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Statistics for data analysis (3+1+1)

1. General Information

This program is designed to train staff with solid statistical knowledge with a focus on the newly recognized field of data science. The curriculum combines rigorous statistical theory with broader practical experience in applying statistical models to data work. Graduates will be in high demand. Most students are expected to be employed as statisticians, analysts and data experts within private and public institutions providing statistical consultations.

Name of the proposer: University "Ss. Cyril and Methodius University in Skopje, Faculty of Information Sciences and Computer Engineering - FINKI
Title of the study program: Second cycle academic studies in Statistics for Data Analysis
Scientific-research area: technical-technological / natural mathematical
Field: Informatics / Mathematics
Areas: Mathematical Statistics and Operations Research, Data Processing, Applied Mathematics and Mathematical Modeling, Programming, Artificial Intelligence, Algorithms, Information Processing .
The value of postgraduate studies is 120 ECTS credits.
Duration of studies: 4 semesters .
One academic year consists of two semesters lasting 30 weeks (1 semester = 15 weeks).
Requirements for enrollment : according to the competition announced by the university, completed undergraduate studies in information science, computer or related fields with a minimum of 180 credits.
Introductory Layer : The introductory layer is the first two semesters in which students are offered a set of differential introductory courses. After their successful realization, the student acquires the right to continue with the second year of postgraduate studies.
Third semester: 3 Mandatory courses and 2 electives, one of which may be from the University list.
Fourth semester : 1 Mandatory course and 1 elective course, the elective course can be from the University list (only if in the first semester the courses are selected at the Faculty level) and the final project - master's thesis from 18 ECTS.
1 ECTS credit corresponds to 30 hours of total work engagement.
The number of contact hours is 4.
The academic title or degree obtained upon completion of the studies is Master of Science in Information Science - Statistics for Data Analysis

Master of Science in Informatics - Statistics for Data Analytics

2. Introductory layer

The first year of study is the introductory layer for students whose studies lasted less than four years, ie students who gained 180 credits from previous studies. Students must pass differential exams that will enable them to enter the basics of mathematics and computer science needed to successfully complete their studies.

Table 1: List of subjects in the first year of study

РБ	CODE / Subject	Semester	M / E	ECTS
1	Mandatory subject 1 from Table 2	VII	M	6
2	Mandatory subject 2 from Table 2	VII	M	6
3	Mandatory subject 3 from Table 2	VII	M	6
4	Mandatory subject 4 from Table 2	VII	M	6
5	Elective course 1 *	VII	E	6
6	Mandatory subject 5 from Table 2	VIII	M	6
7	Mandatory subject 6 from Table 2	VIII	M	6
8	Mandatory subject 6 from Table 2	VIII	M	6
9	Elective course 5 *	VIII	E	6
10	Selection from the university list of free courses	VIII	E

Elective courses can be selected from the proposed list of courses of the study program (Table 2), or from the proposed lists of courses from the introductory layer of other study programs of the Faculty of Information Sciences and Computer Engineering. The selection of courses should be made in accordance with the previous knowledge of the candidate and the necessary knowledge to continue with the postgraduate studies in statistics for data analysis. When choosing courses, the student should coordinate with the head of the study program. A free choice of subject is also allowed, which is on the university list of subjects for the first year of two-year postgraduate studies.

After the successful completion of all ten courses and 60 credits, the student with previously acquired 180 ECTS credits (or completed three-year studies) continues with the courses from the second academic year of postgraduate studies - Table 3 (III and IV semester).

* Selection from the lists of subjects from the introductory layer of all master studies at the Faculty of Information Sciences and Computer Engineering

Table 2: List of recommended courses in the first year of study

РБ	New code / Subject	Semester	ECTS
1	F18L1W011 Discrete Mathematics	VII / VIII	6
2	F18L1S013 Calculus	VII	6
3	F18L2W006 Probability and statistics	VII	6
4	F18L3W035 Linear Algebra and Applications	VII	6
5	F18L3W008 Introduction to Data Science	VII	6
6	F18L3W161 Social Networks and Media	VII	6
7	F18L3W108 Internet of Things	VII	6
8	F18L3W004 Databases	VII	6
9	F18L3W068 Computing in the Cloud	VII	6
10	F18L3S036 Machine learning	VIII	6
11	F18L3S150 Data Mining	VIII	6
12	F18L3S163 Statistical Modeling	VIII	6
13	F18L3S157 Data warehousing and analytics	VIII	6
14	F18L1S023 Business Statistics	VIII	6
15	F18L3W076 Introduction to time series analysis	VIII	6

Table 3: List of Postgraduate Courses in Statistics for Data Analysis

РБ	CODE / Subject	Semester	M / E	ECTS
1	SNP-Z-1 Data analysis with statistical packages	IX	M	6
2	SDP-Z-3 Bayesian data analysis	IX	M	6
3	SDP-Z-4 Data preparation and research	IX	M	6
4	Elective item from Table 4	IX	E	6
5	Elective item from Table 4	IX	E	6
6	SNP-Z-2 Regression Models	X	M	6
7	Elective item from Table 4	X	E	6
8	Master Thesis	X	M	18

Table 3 lists the electives from the Statistics for Data Analysis study program. In addition to these courses, the student can choose from all elective courses, defined for all study programs, from the second cycle that are serviced by the faculty. It is allowed to choose one elective subject from the university list nand free electives.

Table 4: Optional list of offered items

РБ	New code / Subject	Semester	ECTS
1	Methods of statistical locking	IX	6
2	Concepts and application of big data	IX	6
3	Analysis and forecasting time series	IX	6
4	Advanced algorithms	IX	6
5	Modeling and fusing	IX	6
6	Information Processing in Biological Systems	IX	6
7	Analysis of data from related systems	IX	6
8	Text Data Processing	IX	6
9	Optimization methods	IX	6
10	Data processing in bioinformatics	IX	6
11	Network Analysis	IX	6
12	Ambiental intelligence	IX	6
13	Web of the Future	IX	6
14	Statistical Programming	X	6
15	Statistical Learning	X	6
16	Multidimensional statistical analysis	X	6
17	Numerical methods for data science	X	6
18	Statistical research skills: editing , reporting and visualization of data	X	6
19	Business Analytics	X	6
20	Random processes	X	6
21	Big Data Modeling and Management	X	6
22	Discovering knowledge in big graph data	X	6
23	Open and related data	X	6
24	Modern Simulations and Modeling	X	6
25	Computational paradigms in the Internet of Things	X	6
26	Data analysis from mobile sensors / sources	X	6
27	Intelligent mobile applications	X	6

The student can choose a subject from the list of offered elective courses from all study programs of the second cycle of studies. The list of offered electives can be found on this link .

IT Management (4+1)

IT Management (4 + 1)

1. General Information

Postgraduate studies in Management in Information Technology aim to provide quality and top European education and training of highly educated staff with in-depth knowledge of methods and techniques for managing ICT projects and systems. Upon completion of their studies, these staff will be able to take responsible positions in the processes of planning, design, management and monitoring of ICT projects and systems, including their business aspects.

The program in Management Studies in Information Technology is compatible with the relevant studies offered at most of the world's universities that support this topic and enable student mobility.

Name of the proposer: University "Ss. Cyril and Methodius University in Skopje, Faculty of computer science and engineering - FCSE
Study Program Name: IT Management
Scientific-research area: 2 technical-technological
Field
The value of postgraduate studies is 60 ECTS credits .
Duration of studies: 2 semesters .
One academic year consists of two semesters lasting 30 weeks (1 semester = 15 weeks).
Admission Requirements : Students in Information Technology Management can enroll in graduate students who have 240 or 180 undergraduate credits.
Introductory layer : Students who have earned less than 240 credits during their studies are offered a variety of introductory courses. After their successful realization, the student acquires the right to continue with the first semester of postgraduate studies.
First semester: 2 compulsory courses, 2 elective courses in the field.
Second semester: 1 compulsory subject in the field, 1 elective subject in the field and 1 elective subject from the list of UKIM and final project - master's thesis (18 ECTS)
1 ECTS credit corresponds to 30 hours of total work engagement
The number of contact hours is 4

Upon successful completion of the postgraduate studies in Information Technology Management, the successful student will possess the following general abilities and qualifications:

Ability to work in interdisciplinary teams
Power of analysis and synthesis
Power to apply knowledge in practice
Power to generate new ideas (creativity)
Power of learning
Ability to critique and self-critique
Ability to make decisions
Knowledge of English
Research skills

Upon successful completion of the postgraduate studies in Information Technology Management, the successful student will possess the following specific abilities and qualifications:

Knowledge and Understanding	Provides in-depth knowledge and understanding of the theoretical foundations of software and innovation project management, information systems and risk management and other disciplines. Acquiring the necessary knowledge in the field of management with ICT systems and projects. Develop advanced skills in planning, designing, designing, managing, testing, and implementing ICT systems and projects. Demonstrates a high level of professional competence in the analysis of empirical data in the fields of business, industry, economics and government. Work with applied projects to manage projects, resources, money and people. Governs the latest industry standards and best practices, as well as opportunities for improvement and future development in the area.
Applying knowledge and Understanding	Can apply knowledge and understanding for professional development in a narrower area of Information Technology Management. Demonstrates skills and knowledge necessary for the individual to be competent in managing IT systems and projects at a high level. The competencies qualify him with a solid management and technical basis with the possibility to include a selected range of broader aspects of Management in Information Technology and the like that will suitthe needs of the professional in this field with constant and rapid development. In-depth management knowledge required for efficient work of ICT manager, independent specialist or member of specialized team.
Ability to evaluate	Demonstrates a commitment to self-improvement and continuous professional development Demonstrates in-depth knowledge of advanced analysis and design techniques in the fields of Information Technology Management. Demonstrates knowledge of best practices for improving productivity and mutual understanding in business organizations taking into account personal, social, scientific and ethical aspects. Demonstrates the ability to make managerial decisions independently and link business practice with application solutions.
Communication Skills	Demonstrates the ability to communicate with colleagues and work in a team through a high level of awareness of the importance and power of communications. Illustrates effective exchange of information, ideas and reasoned arguments. Demonstrates high ability to work and lead multidisciplinary teams Demonstrates ability to plan and manage time at managerial level and professional socialization and conflict resolution. Recognizes complex organizational structures and the need to restructure them, understands their impact on effectiveness and efficiency in combination with modern technologies.
Learning Skills	Demonstrates an understanding of the basics of research methodology, with the ability to evaluate, design and conduct research in the field, formulate, plan a research project and communicate in depth on a topic. Demonstrates the ability to reasonably evaluate and generate ideas with creative and critical thinking, mastering new theories, models, techniques and technologies, while appreciating the need for continuous professional development. Able to select and understand procedures and methods for structuring, consolidating, and handling information and data in an environment. Has high self-confidence and independence, proactivity and self-awareness to perform and delegate tasks and manage further career.

Acquired title: Master of Information Science and Computer Engineering in the field of Information Technology Management.

2. Studies

Table 1: Schedule of the courses in semesters and academic study years (AC)

List Number	Course code	Course title	Semester	Weekly fund of classes		ECTS
List Number	Course code	Course title	Semester	L	E	ECTS
FIRST YEAR
1.	IT-I-03	ICT Management	9	4	0	6
2.	ITMWE02	Advanced ICT Innovation and Entrepreneurship	9	2	1	6
3.	ITMWE01	Advanced Software Project Management	9	4	0	6
4.		Elective course	9			6
5.		Elective course	9			6
6.	ITMSE01	Advanced Software Requirements Engineering	10	2	0	6
7.		Elective course	10			6
8.		Master's Thesis	10			18
Total hours (lectures / exercises) and number of ECTS credits in the academic year						60

2.1 Electives

Configure

The student can choose a subject from the list of offered elective subjects from all study programs of the second cycle of studies. The list of offered elective courses can be found at this link .

Number	Code	Name of the object	Semester	Weekly fund of classes		ECTS	Unit
Number	Code	Name of the object	Semester	L	E	ECTS	Unit
1	ITMWE07	Management of Databases	9	2	2	6	FINKI
2	ITMWE06	Information security management	9	2	1	6	FINKI
3	SI-Z-01	Software Lifecycle Management	9	4	0	6	FINKI
4	BK-I-12	Change and risk management	9	4	0	6	FINKI
5	ITMWE10	Managing the Software Testing Process	9	2	1	6	FINKI
6	CC-I-02	Big Data and Distributed Data Analytics	9	2	2	6	FINKI
7	ITMWE03	Advanced Management Information Systems	9	2	2	6	FINKI
8	ITMWE08	e-Government advanced topics	9	3	1	6	FINKI
9	ITMWE04	Business Design Thinking	9	4	0	6	FINKI
10	ITMWE11	Digital Transformation	9	2	2	6	FINKI
11	IT-I-04	E-business	9	4	0	6	FINKI
12	IT-I-10	Internet Infrastructure management	9	4	0	6	FINKI
13	EI-I-01	Requirements Analysis in Ecosystem informatics	9	3	0	6	FINKI
14	IS-I-07	Systems for data-based business decision	9	4	0	6	FINKI
15	KN-I-10	Business process mining	9	4	0	6	FINKI
16	SDP-Z-4	Wrangling and exploratory data analysis	9	4	0	6	FINKI
17	IS-I-06	Information Systems Analysis and Design	9	4	0	6	FINKI
18	IT-I-18	Data Science	9	4	0	6	FINKI
19	SNP-Z-1	Data Analysis Using Statistical Packages	9	4	2	6	FINKI
20	CC-I-04	Business modelling	9	4	0	6	FINKI
21	IS-I-01	Collective Intelligence	9	4	0	6	FINKI
22	ITMWE09	Human resource management	9	2	0	6	FINKI
23	SI-I-05	Model based software Engineering	9	4	0	6	FINKI
24	SI-I-07	Engineering ethics	10	4	0	6	FINKI
25	SI-I-08	Engineering ERP business Systems	10	4	0	6	FINKI
26	ITMSE02	IT Service Management	10	2	0	6	FINKI
27	CC-I-07	Small business management	10	3	0	6	FINKI
28	CI-I-11	Decision support systems	10	4	0	6	FINKI
29	SI-I-13	Software Architectures	10	4	0	6	FINKI
30	ITMSE05	Strategic management in IT	10	2	0	6	FINKI
31	EDU-I-10	Student Involvement in Humanitarian, Free and Open-Source Software Development	10	2	2	6	FINKI
32	ITMSE06	Management of Electronic Educational Systems	10	2	1	6	FINKI
33	IT-I-08	Digital Marketing	10	4	0	6	FINKI
34	EDU-Z-04	Gaming in education	10	2	2	6	FINKI
35	EDU-I-04	Recommender Systems, Virtual Guidance and Self- Help in Knowledge Mastery	10	2	2	6	FINKI
36	ITMSE07	Data Science Project Management	10	2	1	6	FINKI
37	SDP-I-4	Business analytics	10	2	2	6	FINKI
38	SI-I-09	Software Reliability	10	4	0	6	FINKI
Total:

IT Management (3 +1+1)

IT Management (3 + 1 + 1)

1. General Information

Postgraduate studies in Information Technology Management aim to provide quality and top European education and training of highly educated staff with in-depth knowledge of methods and techniques for managing ICT projects and systems. Upon completion of their studies, these staff will be able to take responsible positions in the processes of planning, design, management and monitoring of ICT projects and systems, including their business aspects.

The program in Management Studies in Information Technology is compatible with the relevant studies offered at most of the world's universities that support this topic and enable student mobility.

Name of the proposer: University "Ss. Cyril and Methodius University in Skopje, Faculty of Information Sciences and Computer Engineering - FINKI
Study Program Name: Information Technology Management
Scientific-research area: 2 technical-technological
Field
The value of postgraduate studies is 60 ECTS credits .
Duration of studies: 2 semesters .
One academic year consists of two semesters lasting 30 weeks (1 semester = 15 weeks).
Admission Requirements : Students in Information Technology Management can enroll in graduate students who have 240 or 180 undergraduate credits.
Introductory layer : Students who have earned less than 240 credits during their studies are offered a set of differential introductory courses. After their successful realization, the student acquires the right to continue with the first semester of postgraduate studies.
First semester: 2 mandatory courses, 2 elective courses in the field.
Second semester: 1 mandatory subject in the field, 1 elective subject in the field and 1 elective subject from the list of UKIM and final project - master's thesis (18 ECTS)
1 ECTS credit corresponds to 30 hours of total work engagement
The number of contact hours is 4

Upon successful completion of the postgraduate studies in Information Technology Management, the successful student will possess the following general abilities and qualifications:

Ability to work in interdisciplinary teams
Power of analysis and synthesis
Power to apply knowledge in practice
Power to generate new ideas (creativity)
Power of learning
Ability to critique and self-critique
Ability to make decisions
Knowledge of English
Research skills

Upon successful completion of the postgraduate studies in Information Technology Management, the successful student will possess the following specific abilities and qualifications:

Knowledge and Understanding

Provides in-depth knowledge and understanding of the theoretical foundations of software and innovation project management, information systems and risk management and other disciplines.

Acquiring the necessary knowledge in the field of management with ICT systems and projects.

Development of advanced skills in planning, design, design, management, testing, and implementation of ICT systems and projects.

Demonstrates a high level of professional competence in the analysis of empirical data in the fields of business, industry, economics and government.

Work with applied projects to manage projects, resources, money and people.

Governs the latest industry standards and best practices, as well as opportunities for improvement and future development in the area.

Applying knowledge and understanding

Can apply knowledge and understanding for professional development in a narrower area of Information Technology Management.

Demonstrates skills and knowledge necessary for the individual to be competent in managing IT systems and projects at a high level.

The competenciesQualify with solid management and technical foundation with the ability to include a selected range of broader aspects of Management in Information Technology and the like that will meet the needs of the professional in this field with constant and rapid development.

In-depth management knowledge required for effective work of ICT manager, independent specialist or member of specialized team.

Ability to evaluate

Demonstrates a commitment to self-improvement and continuous professional development

Demonstrates in-depth knowledge of advanced analysis and design techniques in the fields of Information Technology Management.

Demonstrates knowledge of best practices for improving productivity and mutual understanding in business organizations taking into account personal, social, scientific and ethical aspects.

Demonstrates the ability to make managerial decisions independently and link business practice with application solutions.

Communication Skills

Demonstrates the ability to communicate with colleagues and work in a team through a high level of awareness of the importance and power of communication.

Illustrates effective exchange of information, ideas and reasoned proposals.

Demonstrates high ability to work and lead multidisciplinary teams

Demonstrates ability to plan and manage time at managerial level and professional socialization and conflict resolution.

Recognizes complex organizational structures and the need to restructure them, understands their impact on effectiveness and efficiency in combination with modern technologies.

Learning Skills

Demonstrates an understanding of the basics of research methodology, with the ability to evaluate, design and conduct research in the field, formulate, plan a research project and communicate in depth on a topic.

Demonstrates the ability to reasonably evaluate and generate ideas with creative and critical thinking, mastering new theories, models, techniques and technologies, while appreciating the need for continuous professional development.

Able to select and understand procedures and methods for structuring, consolidating, and handling information and data in an environment.

Has high self-confidence and independence, proactivity and self-awareness to perform and delegate tasks and manage further career.

Acquired title: Master of Information Science and Computer Engineering in Information Technology Management. & Nbsp;

2. Introductory layer

The introductory layer is intended for students who study for less than four years or have earned less than 240 credits from previous studies.

Table 1: List of introductory layer items

	Code	Subject	Weekly fund	Semester	ECTS
1	CSEW501	Management Information Systems *	2 + 2 + 1	winter	6
2	CSEW705	Innovation in ICT *	2 + 1 + 2	winter	6
3		Selected from Table 2		winter	6
4		Selected from Table 2		winter	6
5		Selected from Table 2		winter	6
6	CSES811	Entrepreneurship *	2 + 1 + 2	summer	6
7	CSES634	ICT Project Management *	2 + 2 + 1	summer	6
8		Selected from Table 2		summer	6
9		Selected from Table 2		summer	6
10		Elective **		summer	6

* If the student has passed the course in his / her undergraduate studies, he / she will have to choose another course from the list of elective courses from the introductory layer (Table 2).

** The course can be selected from the list of electives from Table 2 or from the university list of free electives

Table 2: List of introductory electives

	Code	Subject	Weekly fund	Semester	ECTS
1	CSEW528	User support	2 + 1 + 2	winter	6
2	CSEW505	Software requirements analysis	2 + 2 + 1	winter	6
3	CSEW701	Information Systems Analysis and Design	2 + 2 + 2	winter	6
4	CSEW704	Design of integrated systems	2 + 1 + 2	winter	6
5	CSEW511	Software design and architecture	2 + 1 + 2	winter	6
6	CSEW514	Implementation of Free and Open Source Systems	2 + 1 + 2	winter	6
7	CSEW515	Computer Ethics	4 + 0 + 0	winter	6
8	CSEW310	Marketing	2 + 2 + 1	winter	6
9	CSES631	Software quality and testing	2 + 1 + 2	summer	6
10	CSES625	IS development process	2 + 2 + 2	summer	6
11	CSES612	Electronic & Mobile Commerce	2 + 2 + 2	summer	6
12	CSES610	e-Government	2 + 1 + 2	summer	6
13	CSES617	Business Process Modeling	2 + 1 + 2	summer	6
14	CSES606	Geographic Information Systems	2 + 1 + 2	summer	6
15	CSES205	Business and Management	2 + 2 + 1	summer	6
16	CSES628	Service Oriented Architectures	2 + 2 + 2	summer	6
17	UKIM-I	Selection from University list of free courses

After successfully completing all ten courses and achieving 60 credits, the student with previously acquired 180 ECTS credits (or completed three-year studies) continues with the subjects from the second academic year of postgraduate studies.

3. Studies

Table 1: List of Postgraduate Courses

	Code	Item name	Status	Semester	ECTS	П	А	Л
1	ITMW01	Advanced software project management	M	winter	6	2	1	0
2	ITMW02	Advanced ICT Innovation and Entrepreneurship	M	winter	6	2	1	0
3		Elective	E	winter	6
4		Elective	E	winter	6
5		Elective	E	winter	6
6	ITMS01	Advanced Software Requirements Engineering	M	summer	6	2	1	0
7		Elective	E	summer	6
8		Master Thesis	M	summer	18

3.1 Elective Courses

Configure

The student can choose a subject from the list of offered elective subjects from all study programs of the second cycle of studies. The list of offered elective courses can be found at this link.

09/07/2025

Senior Fullstack Engineer (MSA)

Location: Skopje office

Apply at https://job-boards.eu.greenhouse.io/proton/jobs/4392372101

Join Proton and build a better internet where privacy is the default

At Proton, we believe that privacy is a fundamental human right and the cornerstone of democracy. Since our inception in 2014, founded by a team of scientists from CERN, we have dedicated ourselves to providing free and open-source technology to millions worldwide, ensuring access to privacy, security, and freedom online.

Our journey began with Proton Mail, the largest secure email service globally, and has since expanded to include Proton VPN, Proton Calendar, Proton Drive, and Proton Pass. These tools empower individuals and organizations to take control of their personal data, break away from Big Tech’s invasive practices, and defeat censorship. Our work impacts hundreds of millions of lives, from activists on the front lines defending freedom to leaders in governments protecting sensitive information. In some cases, Proton’s services have even been instrumental in saving lives by enabling secure and private communications in high-risk situations.

Proton is a profitable company that does not rely upon VC funding, supporting over 100 million user accounts with a growing team of over 500 people from over 50 different countries, from the world's top companies and universities. We value intelligence, learning potential, and ambition in our hiring process. Adaptability is key as we navigate uncharted territories and redefine how business is conducted online.

Hiring at Proton is highly selective, with less than 1% of candidates hired. We believe smaller teams of exceptional talent will always prevail over larger teams with lower talent density. You will have the opportunity work with many of the world's top minds in their fields, ranging from former international math and science olympiad winners to chess champions.

We have a global mindset and big ambitions but remain a start-up at heart. We value empowerment and flexibility and keep our structure flat to keep moving fast and avoid unnecessary politics. Tired of blending into the crowd? Join us and do work you can truly be proud of. Check our open-source projects here!

Purpose of the role

MSA is a highly multi-disciplinary group started in 2019 to tackle difficult mail delivery, spam, abuse, and account security problems that impact the Proton ecosystem. We built sophisticated systems from scratch that combine human intelligence and machine learning to make tens of millions of realtime or asynchronous decisions each day. As of late 2023, our areas of focus are 1) mail delivery and spam, 2) abuse and account security, 3) site reliability of Proton, and 4) a new product involving blockchains. Over the past few years, our custom systems have reduced spam filter misclassifications by over 60%, blocked millions of abusive bulk signups, protected hundreds of thousands of users from account compromise by attackers, and mitigated hundreds of DDoS attacks. In order to move fast with limited resources, we are organized into autonomous teams responsible for the whole system, with expertise across infrastructure, data storage, backend, web and mobile apps, machine learning, security and operational excellence. In 3 years, we grew from 2 engineers to over 30 engineers and analysts, spread across 3 continents for 24/7 coverage. We are looking for humble, mission-driven, systems-thinking people who want to make a big impact in a startup environment.

What you will do

MSA builds and operates many services responsible for different domains. You will:

work with other engineers and analysts to design, build, and operate these systems
work on special user-facing features involving frontend and backend software development
You will have the opportunity to play Product or Project Managers roles and lead the whole planning and development process
be responsible for the operational excellence of the systems/features and their interaction with other systems
You may work on MSA's custom systems written in Python or on the main Proton API written in PHP or on Proton Web apps written in React or even on native iOS and Android mobile apps

Job requirements

Familiar with backend development (Python, PHP, or Go)
Familiar with frontend design and development (JavaScript, React, Typescript, or jQuery)
Familiarity with building complex production systems
Familair with data processing and storage (MySQL, MongoDB, Redis, Kafka, Elastic, Ceph, ClickHouse)
Excellent English communications, both written and spoken

Bonus points for:

experience with machine learning and real-time prediction systems
experience with iOS or Android app development
experience with managing Linux servers, including infrastructure as code (Puppet, Ansible) and containerization

What We Offer

Office First: Collaboration is easier and more effective in person, which is why we have offices in Geneva, Zurich, Prague, Barcelona, Paris, London, Vilnius, Skopje, and Taipei. You can also enjoy working from home up to 30% of the time, while enjoying great company during our three core days in the office. Depending on the role, fully remote positions may also be available.
Technology: We provide all the devices and software you need to excel in your role, ensuring you have the best tools at your disposal to achieve your goals.
Food: Lunch and snacks are provided by Proton every day at our offices.
Transport: We will always support our employees with transport costs through subsidizing public transport, bike allowances, or parking spaces based on your office location.
Stock Options: At Proton, we are all owners of the company and you get stock options when you join us.
Flexible Working: You can define your own working hours as long as it works with team meetings.
Learning and Development: We are committed to your professional growth. Proton offers various learning opportunities, including training programs, conferences and events, and continual learning.
Employee Benefits: Comprehensive health insurance plans, competitive retirement savings options, generous vacation and leave policies, and wellness programs.
Work that Matters: Proton is a community-first organization, started with the support of a crowdfunding campaign and built with community input. To this day, Proton’s only source of revenue is user subscriptions. Over 100 million people trust and support Proton, and we put our users and community first in everything we do. Read more about our impact here.

Our Commitment to Diversity and Inclusion

At Proton, we believe diversity drives innovation and strengthens our mission to provide privacy as a default for all. We are committed to fostering an inclusive environment where all individuals, regardless of race, ethnicity, gender, age, sexual orientation, physical ability, or socio-economic background, feel valued and empowered. We strive to create equal opportunities, promote open dialogue, and support continuous learning to ensure every voice is heard and respected.

If you need any extra support or reasonable adjustments during the hiring process, please let your talent partner know.

Candidate Privacy Notice

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Табови

Summary

ana.madevska@finki.ukim.mk

Summary

Родена е 1967 година во Скопје. Основно и средно образование завршила во Скопје. Во 1991 година дипломирала на Институтот за информатика при ПМФ во Скопје како најдобар дипломиран студент во тековната академска година. На Институтот за информатика почнала и да работи како стручен соработник во 1992 година. Во 1996 година магистрирала на темата „Модификација на повеќеслојни невронски мрежи без повратни врски и нивно изучување“ (магистер по информатички науки), а во 2003-тата ја одбранила докторската дисертација под наслов “Препознавање облици со примена на машините со поддржувачки вектори и повеќеслојните невронски мрежи без повратни врски“ (доктор на информатички науки), на ИИ, ПМФ. Од пролетта 2004 работи како доцент на Институтот за информатика и држи настава по предметите: интелигентни системи, биоинформатика, основи на оперативните системи, основи на програмирање, објектно и визуелно програмирање, методика на информатичката настава, практикум, информациски технологии во образованието. Наставник е и на постдипломските студии по информатика и биологија. Главно подрачје на научен интерес на проф. Мадевска-Богданова е областа на вештачките интелигентни системи - препознавање облици, биоинформатика, податочно рударење, а работи и на формализираното претставување на знаење и на методиката на наставата по информатика. Објавила 40-тина трудови од областите на нејзиниот интерес во книги списанија со импакт фактор, меѓународни списанија и зборници на трудови од меѓународни и домашни конференции. Досега објавила неколку учебни помагала, како и материјали за сите курсеви кои ги одржувала. Била уредник во списанието Бит+, во издание на ИИ. Учествувала во вкупно 7 домашни и 8 меѓународни научноистражувачки проекти. Мадевска-Богданова престојувала на неколку странски универзитети. Ги следела Интернационалната летна школа за когнитивна наука во Софија и ERASMUS програмата за математички методи во технологијата во Антверпен, Белгија. Во рамките на TEMPUS проект имала 3-месечен престој во Лувен, Белгија. Во текот на последните 15 години неколку пати имала стручен престој на Католичкиот универзитет во Лувен, Белгија, и на Мастрихт -универзитетот, Холандија. Била поканет предавач на Универзитетот во Мејн, САД. Во 2003-2005 година била раководител на Компјутерскиот центар на ИИ, а од 2005-2009 година била раководител на Заводот за програмско инженерство и раководела со активностите за промоција на ИИ. Почнувајќи од 2009-та година, таа е Раководител на Институтот за информатика. Член е на Здружението на информатичарите на Македонија и во неколку наврати била претседател на комисии за натпревари. Член е на Европското здружение за невронски мрежи.

Рецензија - ЛИНК.
Одлука за избор - ЛИНК

Presentations

Презентација за	На конференцијата	Од тип
Data mining -можност за предвидување	DEKUS 2000	Научна
Data mining in Bioinformatics	DECUS 2004	Научно
DNA chips and Microarrays in Bioinformatics	HP Interex конференција 2005	Научно
Support Vector Machines as pattern classificator in Bioinformatics	Conference on Informatics and Information Technology	Научна
SVM classifiers with moderated outputs for automatic classification in Molecular Biology	Conference on Informatics and Information Technology	Научна
Teaching Bioinformatics to Computer Science Students	EUROCON 2005
On Object Oriented modeling - Why and how	DAAD Workshop on Software Engineering, Ivanjica, September 2010	Workshop
Design Patterns in the course ‘OOP in Java’	DAAD Workshop on Software Engineering, Neum, BiH, September 2009	Workshop

Associations

Линк до асоцијацијата (здружението)	Име на асоцијацијата (здружението)
http://www.ieee.org/	IEEE
http://cs.org.mk	Здружение на информатичарите на Македонија
ict-act.org	ICT ACT

Books

Наслов на книгата	Издавач
A Different Approach to Information Technology - Teaching the Intelligent Systems Course, in "Technology, Education and Development"	InTech

Publications

Име на трудот	Место	Држава
Pruning nodes in feedforward Neural Networks	Proceedings of the VIII-th International konference of logics and informatics LIRA '97	Jugoslavija
Application of Neural Networks in Simulation of Hydrological sets	Proceedings of XXI International Conference on Information Technology Interfaces ITI'99	Croatia
Analysis of the MSVMO method - the probabilistic SVM outputs	Proceedings of 26-th International Conference on Information Technology Interfaces	Croatia
NN Probabilistic Outputs in Character Recognition Problem	Proceedings of the II-nd Balkan Conference	Macedonia
Paralelna implementacija na Dirihleova tesalacija	4-ти тематски ЕТАИ	Македонија
Feedback transducer - neperiodiцni nizi dobieni so koneцni avtomati	Proceedings 4-ти тематски ЕТАИ	Македонија
Algotithms for Dirichlet Tessellation	Proceedings of VII conference of logic and informatics LIRA '95	Jugoslavija
Data scaling in Feedforward Neural Networks	Proceedings of XIX International Conference Information Technology Interfaces ITI'97	Croatia
Automatic Classification With Support Vector Machines In Molecular Biology	Proceedings of III International conference of Cognitive and Neural sytems	USA
A geometrical modification of SVM outputs for pattern recognition	Proceedings of XXII International Conference on Information Technology Interfaces ITI'00	Croatia
A new approach of modifying SVM outputs	Proceedings of IEEE-INNS-ENNS International Joint Conference on Neural Networks IJCNN'2000	Italy
Support Vector Machines as pattern classificator in Bioinformatics	Proceedings of Second CIIT'01	Macedonia
SVM classifiers with moderated outputs for automatic classification in Molecular Biology	Proceedings of Third Conference for Information Technology, CIIT’2002	Macedonia
Pattern recognition in DNA sequences using SVM classifiers with probabilistic outputs	Proceedings of Mathematics and Informatics for Industry International Conference – MII 2003	Greece
Classification of DNA sequences using modified SVM outputs	Proceedings of 13-ta International Conference of Artificial Neural Networks, ICANN /IJCNN	Turkey
Recognition of human mitochondrial sequences using SVM	Proceedings of The First Balcan Conference of Informatics, BCI’2003	Greece
Pattern recognition using Support vector machines and Multylayered feedforward Neural Networks	PhD Thesis	Macedonia
Learning system based on digital games	CIIT	Macedonia
Overview of modern file systems	CIIT	Macedonia
SA Tabu Miner - A Hybrid Heuristic Algorithm For Rule Induction	URPDM	Portugal
System for Management,Visualization and Maintenance of Infrastructural Resources	TELFOR-2010	Serbia
An application for geospatial visualization of optical networks	ICEST	Macedonia
An Application for Maintaining Optical Networks	ICT-Innovation	Macedonia
Intelligent Systems – the Course	Proceedings of Computational Intelligence and Information Technologies CIIT’08	Macedonia
Morphosyntacic Annotation of Macedonian Language using Support Vector Machines	Proceedings of 30th MIPRO	Croatia
DNA chips in bioinformatics	Proceedings of Computational Intelligence and Information Technologies CIIT’07	Macedonia
Expert System for Taxonomy in Entomology	proceedings 10th World Multiconference on Systemic, Cybernetics and Informatics (WMSCI 2006)	USA
Teaching Bioinformatics to Computer Science Students	Proceedings of IEEE EUROCON 2005	Serbia and Montenegro
MULTICATEGORY SUPPORT VECTOR MACHINES FOR CLASSIFICATION OF HUMAN URINARY CALCULI	Proceegings of 14th International Symposium Spectroscopy in Theory and Practice	Slovenia
NN Probabilistic Outputs in character recognition problem	Proceedings of The Second Balcan Conference of Informatics, BCI’2003	Macedonia
Analysis of the MSVMO method - the probabilistic SVM outputs	Proceedings of International Conference on Information Technology Interfaces	Croatia
Probabilistic SVM outputs for pattern recognition using Analytical Geometry	NEUROCOMPUTING, An International Journal, Elsevier
Bioinformatics – the Machine Learning approach	Proceedings of Fourth Conference for Information Technology, CIIT’2003	Macedonia
Recognition of human mitochondrial sequences using SVM	Proceedings of The First Balcan Conference of Informatics, BCI’2003	Greece
Classification of DNA sequences using modified SVM outputs	of 13-th International Conference of Artificial Neural Networks, ICANN /IJCNN	Turkey
Pattern recognition in DNA sequences using SVM classifiers with probabilistic outputs	Proceedings of Mathematics and Informatics for Industry International Conference – MII	Greece
SVM classifiers with moderated outputs for automatic classification in Molecular Biology	Proceedings of Third Conference for Information Technology, CIIT’2002	Macedonia
Automatic classification in Molecular Biology using SVM classifiers	Proceedings of NATO Advanced Study Institute on Learning Theory and Practice	Belgium
Support Vector Machines as pattern classificator in Bioinformatics	Proceedings of Second Conference for Information Technology, CIIT’2001	Macedonia
A new approach of modifying SVM outputs	Proceedings of IEEE-INNS-ENNS International Joint Conference on Neural Networks	Italy
A geometrical modification of SVM outputs for pattern recognition	Proceedings of Conference on Information Technology Interfaces, ITI 2000	Croatia
Automatic Classification With Support Vector Machines In Molecular Biology	Proceedings of the Third annual conference on Cognitive and Neural Systems	USA
Application of Neural Networks in Simulation of Hydrological sets	Proceedings of the XXI International Conference on Information Technology Interfaces	Croatia
Data scaling in Feedforward Neural Networks	Proceedings of the XIX-th International Conference in Information Technology Interfaces	Croatia
Pruning nodes in Feedforward Neural Networks	Proceedings of the VII-th International Conference in Logic and Computing, LIRA 97	Yugoslavia
Sequentional and parallel algorithms for Dirichlet Tessalation	Proceedings of VIII-th Conference in Logic and Computing, LIRA 95	Yugoslavia
Parallel implementation of Dirichlet Tessalation	Proceedings of Balkan Conference, ETAI	Macedonia
Feedback transducer - nonperiodical arrays with finite automata	Proceedings of Balkan Conference, ETAI	Macedonia

Conferences

Назив на конференцијата	Име на конференцијата	Град	Држава
DEKUS 2000	DEKUS	Охрид	Македонија
DECUS 2004	DECUS	Охрид	Македонија
HP Interex конференција 2005	HP Interex конференција 2005	Охрид	Македонија
Conference on Informatics and Information Technology	CIIT	Битола	Македонија
EUROCON 2005	Computer as a Tool	Belgrade	Serbia and Montenegro
	18. telekomunikacioni forum, TELFOR 2010	Belgrade	Serbia
7th Conference for Informatics and Information Technology	CIIT 2010	Bitola	Macedonia
New Support Vector Machines-based approach over DNA chip data	INNOVATIONS 2008	Al Iin	UAE
Intelligent Systems for Computer Science Students	INTED 2008	Valencia	Spain
Intelligent Systems – the Course	Computational Intelligence and Information Technologies CIIT’08	Bitola	Macedonia
Morphosyntacic Annotation of Macedonian Language using Support Vector Machines	30th MIPRO	Opatija	Croatia
DNA chips in bioinformatics	Computational Intelligence and Information Technologies CIIT’07	Bitola	Macedonia
Expert System for Taxonomy in Entomology	10th World Multiconference on Systemic, Cybernetics and Informatics (WMSCI 2006)	Orlando	USA
MULTICATEGORY SUPPORT VECTOR MACHINES FOR CLASSIFICATION OF HUMAN URINARY CALCULI	14th International Symposium Spectroscopy in Theory and Practice	Nova Gorica	Slovenia
NN Probabilistic Outputs in character recognition problem	The Second Balcan Conference of Informatics, BCI’2003	Ohrid	Macedonia
Analysis of the MSVMO method - the probabilistic SVM outputs	International Conference on Information Technology Interfaces	Cavtat	Croatia
Bioinformatics – the Machine Learning approach	Fourth Conference for Information Technology, CIIT’2003	Bitola	Macedonia
Recognition of human mitochondrial sequences using SVM	The First Balcan Conference of Informatics, BCI’2003	Thessaloniki	Greece
Classification of DNA sequences using modified SVM outputs	13-th International Conference of Artificial Neural Networks, ICANN /IJCNN	Istanbul	Turkey
Pattern recognition in DNA sequences using SVM classifiers with probabilistic outputs	Mathematics and Informatics for Industry International Conference – MII	Thessaloniki	Greece
SVM classifiers with moderated outputs for automatic classification in Molecular Biology	Third Conference for Information Technology, CIIT’2002	Bitola	Macedonia
Automatic classification in Molecular Biology using SVM classifiers	NATO Advanced Study Institute on Learning Theory and Practice	Leuven	Belgium
Support Vector Machines as pattern classificator in Bioinformatics	Second Conference for Information Technology, CIIT’2001	Bitola	Macedonia
A new approach of modifying SVM outputs	IEEE-INNS-ENNS International Joint Conference on Neural Networks	Lake Como	Italy
A geometrical modification of SVM outputs for pattern recognition	Conference on Information Technology Interfaces, ITI 2000	Pula	Croatia
Automatic Classification With Support Vector Machines In Molecular Biology	Third annual conference on Cognitive and Neural Systems	Boston	USA
Application of Neural Networks in Simulation of Hydrological sets	the XXI International Conference on Information Technology Interfaces	Pula	Croatia
Data scaling in Feedforward Neural Networks	the XIX-th International Conference in Information Technology Interfaces	Pula	Croatia
Pruning nodes in Feedforward Neural Networks	the VII-th International Conference in Logic and Computing, LIRA 97	Novi Sad	Yugoslavia
Sequentional and parallel algorithms for Dirichlet Tessalation	VIII-th Conference in Logic and Computing, LIRA 95	Novi Sad	Yugoslavia
Parallel implementation of Dirichlet Tessalation	Balkan Conference, ETAI	Ohrid	Macedonia
Feedback transducer - nonperiodical arrays with finite automata	Balkan Conference, ETAI	Ohrid	Macedonia

Specializations

Престој	Држава	Цел
Bioinformatics group in SISTA, Electrical Engineering Department, Catholic University	Belgium	On invitation of prof. Yves Moreau, collaboration with Bioinformatics group
NATO - ASI 'Learning theory and practice'	Belguim	Participation in NATO learning module, poster presentation
Human Genetics Department, Universiry of Maastricht	Netherlands	Presentation, 'SVM in Bioinformatics'
Visiting the University of Maine	Maine, USA	Presentation, 'SVM in Bioinformatics'
Data mining and Bioinformatics group in SISTA, Electrical Engineering Department, Catholic University	Belgium	Lecture “Support vector machines for pattern recognition”
ESAT - SISTA, Catholic University	Belgium	Developing course modules in Artificial Intelligence
ERASMUS school in Mathematical Mathods in technology	Belgium	ERASMUS programm
International Summer School in Cognitive Science	Bulgaria	Summer School
International Summer School in Cognitive Science	Greece	Developing cooperation
Visit to Humbolt University	Germany	JCSE course development
TEMPUS, CARDS CD JEP 18046-2003 Management and (e)Business Education in Computer Studies	England	Tempus project
TEMPUS, CARDS CD JEP 18046-2003 Management and (e)Business Education in Computer Studies	Greece	Tempus project
Visit to Catholic University	Belgium	Scientist visit
Visit to Catholic University	Belgium	Scientist visit
Tempus CD_JEP-16160-2001	Greece	Developing a course
Visit to Human Genetics Department	Holland	Scientist visit
Visit to Catholic University	Belgium	Scientist visit
University of Maine	Maine, USA	Invited lecture
Visit to Catholic University	Belgium	Tempus mobility grant
Summer School for Cognitive Science	Bulgaria	Attending Courses

Projects

Име на проектот	Финансирано од
DAAD - center of excelence for applications of mathematics; Probabilistic models in mathematical biology and bioinformatics	DAAD
Pattern recognition models using neural networks	Министерство за Наука
System for visualization of network resources	Faculty of electrical engineering and information technology
E-Health applications using folksonomy and Internet social networks	Faculty of electrical engineering and information technology
Software Engineering: Computer Science Education and Research Cooperation	DAAD, Germany
Проект за модернизација на образованието	МОН/Светска банка
TEMPUS, CARDS CD JEP 18046-2003 Management and (e)Business Education in Computer Studies	TEMPUS
Centre of Excellence for Applications of Mathematics, Mathematical models in Bioinformatics	DAAD, Germany
IST EU SEE Project 5th Framework, A Balkan and Eastern European Network of Excellence for the diffusion of Mathematics for Industry	FP6
National Contact-Point of Macedonia for Open and Distance Education	PHARE
Analiza i izrabotka na algoritmi za predviduvawe na vremenski serii	МОН
Математички модели za препознавање облици	МОН
individual mobility grant for developing course modules	TEMPUS
Programski modeli za paralelno procesirawe	МОН
Паралелни архитектури и алгоритми	МОН
Biocybernetical models of computer aided artefacts for dissabled people, hearing an vision	МОН
Computer applications of mathematical disciplines	МОН
Mathematical methods and computer support for the spatial system for Republic of Macedonia	МОН

д-р Ана Мадевска Богданова

10/07/2025

Desktop Engineer (Inbox)

Location: Skopje office (70%)

Apply at: https://job-boards.eu.greenhouse.io/proton/jobs/4634890101

Join Proton and build a better internet where privacy is the default

The Team

The Inbox Business Unit drives the development of Proton Mail (our flagship product line) and Proton Calendar. We are a cross-functional team of (ballpark figure) 60 engineers, product managers, designers and data analysts. We are committed to constantly push the boundaries of what we can achieve. It’s not always an easy journey, but it’s one that offers the chance to create meaningful impact and drive lasting change.

The Inbox Desktop team is responsible for developing desktop clients of Inbox i.e. Proton Mail Desktop App, Proton Mail Bridge, and the Export tool. Because most of these applications are premium offerings of Proton, we put a very high emphasis on product and engineering quality. We are in the process of rebuilding our client applications on a new, innovative technology stack. As part of this technological transformation, we are also restructuring our team, and we are looking for a smart and ambitious Junior Software Development Engineer to strengthen our team by helping on Proton Mail Bridge and the Export tool.

Tech Stack and Tools

Proton Mail Bridge is developed using Golang, C++, Qt, and released on 3 platforms (macOS, Windows, Linux).
All our client-code is open-source and GPL3.
Our backend runs on premise in Proton's data-centers.
To organise our work we use standard tools such as Jira, Confluence, and GitLab.

Purpose of the role

As a Junior Software Development Engineer in the Inbox Desktop team, you will play a crucial role in maintaining one of Proton's most mature desktop offerings, Proton Mail Bridge. We expect you to be customer-centric, continuous learner, passionate about technology and usability. You are an adept at turning technical complexities into seamless user experiences. Effective teamwork, collaboration with Product, Design, APIs, and your team, and data-driven decision-making are essential aspects of this role.

In the Inbox organisation, we believe that a psychologically safe environment is critical to foster innovation, collaboration, and growth. We are rooted in science, and according to both academic research and empirical evidence, teams that feel safe to take risks and express their ideas are more likely to be innovative and perform better: you will play a key role in helping us creating such an environment across the entire organisation.

What you will do

Develop, deploy and support high-quality user experiences on Proton Mail Bridge and the Export tool including existing and new feature development.
Collaborate with QA, designers, and product managers, to make our product better and better.
Work with senior software engineers to learn how to write clear, concise and testable code to maintain and elevate the quality of our codebase.
Analyse the MIME structure of messages and take an active part in test automation.
Strive for frequent releases, write code with growing test coverage and use CI.
Maintain our team and system documentation.
Take part in team activities, such as project meetings, code reviews, and pair programming.
Foster a culture of learning, creativity, and accountability for the best possible work.

Job requirements

While we prefer candidates who cover the entire skillset, do not hesitate to apply if you are not an exact match, as we are willing to help you grow in certain areas.

Coding: Professional software development experience with Golang (a significant portion of the codebase is in Golang) or other object-oriented compiled languages such as C++ or Rust. Familiarity with Qt. Experience with writing automated tests for your code. Comfortable using collaboration and developer efficiency tools such as Git, GitLab, GitHub, IDEs, etc.
Desktop software development: Experience in developing and troubleshooting desktop applications on Windows, macOS, and Linux.
Problem-solving: Strong problem-solving skills and the ability to troubleshoot issues efficiently remotely while protecting our user’s privacy.
Collaborative skills: Proven ability to work collaboratively in a team environment, excellent written communication skills, and experience working in a distributed team setup.
Product mindset: A product mindset with a focus on offering outstanding user experience in a successful business environment.
Security focus: Understanding of secure coding practices and a commitment to maintaining high levels of security and privacy.
Hybrid work environment: Able to work from the office (70%).

Bonus points for:

Bachelor's or Master's degree (or close to completion) in Computer Science, Software Engineering, or a related field.
Awareness of common security issues in client-side development, such as those in the OWASP top ten, and how to mitigate them.
Familiarity with UX, accessibility, internationalisation, and localisation concerns and solutions.
Experience with Grafana or other monitoring platforms.

What We Offer

Office First: Collaboration is easier and more effective in person, which is why we have offices in Geneva, Zurich, Prague, Barcelona, Paris, London, Vilnius, Skopje, and Taipei. You can also enjoy working from home up to 30% of the time, while enjoying great company during our three core days in the office.
Technology: We provide all the devices and software you need to excel in your role, ensuring you have the best tools at your disposal to achieve your goals.
Food: Lunch and snacks are provided by Proton every day at our offices.
Transport: We will always support our employees with transport costs through subsidising public transport, bike allowances, or parking spaces based on your office location.
Stock Options: At Proton, we are all owners of the company and you get stock options when you join us.
Flexible Working: You can define your own working hours as long as it works with team meetings.
Learning and Development: We are committed to your professional growth. Proton offers various learning opportunities, including training programs, conferences and events, and continual learning.
Employee Benefits: Comprehensive health insurance plans, competitive retirement savings options, generous vacation and leave policies, and wellness programs.
Work that Matters: Proton is a community-first organisation, started with the support of a crowdfunding campaign and built with community input. To this day, Proton’s only source of revenue is user subscriptions. Over 100 million people trust and support Proton, and we put our users and community first in everything we do. Read more about our impact here.

Our Commitment to Diversity and Inclusion

If you need any extra support or reasonable adjustments during the hiring process, please let your talent partner know.

Candidate Privacy Notice

If we no longer have a legitimate business need to process your information, we will either delete or anonymise it. Should you have any inquiries about how we use or manage your information, or if you wish to access, correct, or delete your data, please contact our privacy team at careers@proton.ch.

To learn more about our privacy policy, please visit our privacy policy page.

URBANFLOODS

Body:

URBANFLOODS: Strengthening Flood Resilience Across the Adriatic-Ionian Region

URBANFLOODS Logo

URBANFLOODS project aims to raise public awareness, suggests guidelines for flood prevention, and provides strategic action plans for the short, medium, and long term. The project is designed to benefit local authorities, communities, policymakers, and the public, who should consider these recommendations for building more flood-resilient cities in the future.

Project info box

Name of the project: URBANFLOODS: Strengthening Flood Resilience Across the Adriatic-Ionian Region
Source of funding: Interreg IPA-Adrion
Implementation period: from 01/09/2024 to 31/08/2027
Total budget€ - 1.747.583,17 € (80% EU contribution - 85% IPA contribution)
Website: https://urbanfloods.interreg-ipa-adrion.eu/

Project’s description:

The Adriatic-Ionian region, with its unique geographical and climatic conditions, is increasingly susceptible to severe floods due to the combination of climate change and land use. These events have led to significant geomorphological changes in river channels and, historically, have caused considerable damage to lives, property, agriculture, and tourism infrastructure.

The goal of the URBANFLOODS project is to strengthen urban resilience against the growing threat of floods, particularly targeting rivers and streams in urban areas within the Adriatic-Ionian region. By developing an integrated decision support system in accordance with the EU Floods Directive and an innovative communication and learning platform, the project aims to transform flood management and preparedness.

Specific objectives of the project

Joint Development of an Integrated Decision Support System (DSS): Involves creating an advanced data-driven system that offers comprehensive solutions for flood management and early warning systems.
Strengthening Natural and Civil Protection Mechanisms: Focuses on improving existing strategies for natural and civil protection and introducing new measures to further safeguard the Adriatic-Ionian region from flood risks.
Analysis of Established Protocols for Effective Practices, Transnational Strategies, and Action Plans: A process that includes identifying, documenting, and adopting successful flood management strategies and action plans, which can serve as a reference for other regions facing similar challenges.
Education of Local Communities: Aims to enhance the understanding of flood risks among local communities by encouraging a culture of "preparedness" and promoting proactive measures to mitigate potential impacts.

Main expected results

Unified DSS: A single, integrated DSS will enhance the capacity of local authorities to mitigate urban flood risks and increase urban resilience by offering sophisticated, data-driven flood management solutions. This unified DSS will be validated and demonstrated across nine different pilot locations.
Transnational URBANFLOODS Strategy: A comprehensive transnational strategy will be established to achieve efficient and effective flood management. This strategy will provide a shared vision, goals, objectives, policies, actions, and measures, all based on a data-driven approach.
Three Action Plans: Three action plans will be developed to translate the transnational strategy into actionable steps. These plans aim to enhance knowledge and support decision-making across three key categories of institutions: (1) local/regional authorities, (2) civil protection agencies, and (3) national authorities.
Memorandum of Cooperation: A formal agreement among partners to continue collaboration post-project completion. This memorandum will promote knowledge exchange and the transfer of best practices among partners and relevant stakeholders, increasing the visibility of project outcomes to support future synergies and raise public awareness and preparedness, thereby maximizing the project's potential impact.

PARTNERS

University of Western Macedonia, Department of Electrical and Computer Engineering – Greece (EL) – Lead Partner
Hydro-engineering Institute Sarajevo – Bosnia and Herzegovina (BA)
Development centre Murska Sobota – Slovenia (SI)
Macerata Municipality– Italy (IT)
Regional development agency Backa – Serbia (RS)
Municipal Enterprise for Water Supply and Sewerage of Kozani – Greece (EL)
Hydrowater-Albania sh.p.k – Albania (AL)
Rijeka Development Agency Porin Ltd. – Croatia (HR)
Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje – North Macedonia (MK)
EuroMediterranean Center for the Sustainable Development – SVI.MED NPO – Italy (IT)
Center for Knowledge Management CKM – North Macedonia (MK)

Associated partners

Municipality of Scicli – IT
Municipality of Modica – IT
Slovenian Environment Agency (ARSO) – SI
Agency for watershed of the Adriatic Sea – BA
Water Supply and Sewerage Association of Albania – AL
MINISTRY OF ENVIRONMENT AND ENERGY, GENERAL DIRECTORATE FOR WATER – EL
Public Water Management Company “Vode Vojvodine” – RS
Municipality of Kozani – EL
Centre for Crisis Mangement – MK
Institute of Sustainable Development and Management of Natural Resources-UCRI TEMENUS UOWM – EL
Public Institution for protected area management in the Primorje-Gorski Kotar County – HR

Крива Река

News

Information about First National Stakeholders’ Meeting in North Macedonia URBANFLOODS project - Date of publication: 26.3.2025
Information about Second transnational URBANFLOODS Meeting held in Rijeka - Date of publication: 23.4.2025
Kriva Reka: Building flood-resilient communities through URBANFLOODS Project - Date of publication: 20.6.2025
Urban Flooding in North Macedonia: Managing Risk in a Changing Climate - Date of publication: 23.6.2025
New station on the Kriva River Basin for improved urban flood management within the UrbanFloods project - Date of publication: 29.8.2025

Contacts

Boro Jakimovski - boro.jakimovski@finki.ukim.mk
Andreja Naumoski - andreja.naumoski@finki.ukim.mk

The URBANFLOODS project is co-funded by the European Union through the Interreg IPA ADRION Programme.

Languages

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Statistics for data analysis (3+1+1)

IT Management (4+1)

IT Management (4 + 1)

2.1 Electives

IT Management (3 +1+1)

IT Management (3 + 1 + 1)

3.1 Elective Courses