PhD in Computer Science in Europe

This PhD program trains computer science and information and communication technology experts with a solid theoretical foundation, offering regular coursework, preparation for a scientific degree, and teaching experience in higher education. It is organized into doctoral programs covering Software and Computer Science; Data Science, Networks, and Information Systems; Scientific Computing and Models, Numerical and Symbolic Methods; Informatics Teaching Methodology; Geospatial Information and Spatial Data; and IT Solutions in Engineering Sciences. Various scholarships and research opportunities are available to doctoral students.

Supervision is provided by faculty as well as researchers from national research institutes, and training is supported by modern infrastructure, including computer labs equipped for artificial intelligence, database, and robotics research, along with access to a wide range of electronic publications and databases. Bilateral agreements with universities worldwide allow students to spend one or two semesters abroad or take part in research at a partner institution, and students can also participate in EU-funded research and innovation programs and industry-linked doctoral initiatives, working on topics such as 5G edge-computing assessment or quality-of-service frameworks for next-generation networks.

Graduates go on to academic or higher-education positions, or into the software industry, where international companies operating research labs in the region recruit PhD-qualified computer science and ICT experts, and smaller innovative companies hire graduates as project leaders; strong doctoral research can also lead to a marketable product or a private start-up. Typical paths include teaching and research positions in academia, ICT expert roles at companies, or founding a start-up.

Applicants must hold an MSc degree and complete an entrance examination; before applying, it is strongly recommended that applicants discuss their research plan with the relevant professor.

English proficiency must reach B2 level in both speaking and writing; an intermediate, state-accredited language exam is also a condition for admission.

Required documents include an application form, bachelor's and master's degree certificates, a transcript of records, a CV, a research plan, a letter of recommendation, a language certificate, a passport copy and photo, a medical certificate, and a certificate of clean criminal record; applicants planning to conduct their doctoral research at an external institute outside the university must also submit a statement about the research location. The oral entrance exam lasts about 20 minutes and centers on the applicant's research plan and competencies, evaluated by a three-member committee on general professional aptitude, grounding in the chosen field, prior academic performance, undergraduate research experience, the feasibility of the research plan, and language skills.

This PhD program offers advanced research training across several disciplines, including engineering sciences, ICT, mathematical sciences, and natural sciences. It combines theoretical and methodological coursework (minimum 30 ECTS) with supervised original research leading to a doctoral dissertation, trial lecture, and public defense. Specializations include civil and structural engineering, mechatronics, renewable energy, AI, mobile communications, mathematics, mathematics education, molecular biology, and ecology. Each specialization provides tailored courses to support the doctoral work, with research projects often conducted in collaboration with public and private institutions. The program is designed to develop deep expertise and contribute to scientific advancement.

To be eligible for this PhD program, applicants must hold a master’s degree in a relevant subject area from a recognized institution. Admission normally requires a minimum average grade of C or equivalent in the bachelor's degree, and a B or higher for both the master's coursework and thesis. If an applicant does not meet the grade criteria, the hosting research group must justify the candidate’s potential to complete the program, possibly with additional admission conditions. All applicants must demonstrate English proficiency through recognized tests such as TOEFL (minimum 92 iBT or 600 PBT) or IELTS (minimum 6.5), unless exempt under national guidelines.

This doctoral program combines knowledge of computer systems, software development, and technological solutions, preparing students to develop and analyze advanced computing systems, the Internet of Things, cloud computing, cybersecurity, and autonomous systems. Doctoral students work on real-world problems and develop innovative technologies for industrial automation and robotics, applying artificial intelligence throughout their research. Current research topics include penetration-testing methods for assessing the resilience of Internet of Things systems against quantum computing threats, multimodal segmentation of transparent and reflective objects for real-time industrial systems, the use of EEG and EMG signals combined with deep learning for emotion recognition and prediction in virtual reality applications, hybrid optimization methods for robot control using artificial intelligence platforms, risk-based approaches to cyber resilience in secure digital ecosystems, and personalized, non-invasive estimation of glucose dynamics from optical signals taken at the fingertip.

Core coursework centers on methods of information technologies, providing essential grounding in the field. Students can deepen their focus through a wide range of alternative modules covering intelligent business process modelling and simulation, artificial intelligence in information systems, cloud computing technologies, conceptual modelling and knowledge representation, deep learning engineering, hybrid systems for control and optimization, information security technologies, large-scale machine learning, machine learning and neural networks, information visualization methods, multimedia systems, information requirements specification, process modelling and identification, scientific visualization, and systems analysis technologies. Elective modules in academic communication and the fundamentals of research methods further support students' individual development.

Applicants must hold a master's degree or an equivalent higher education qualification in physics, mathematics, or informatics, within the broader fields of technology or natural sciences. Applicants must have the written agreement of a prospective supervisor to take them on if invited to study, must hold at least one scientific publication that has been published or accepted for publication, submitted alongside the application, and must submit a research proposal on their selected topic; applications without a qualifying publication will not be considered.

Admission is based on a weighted competition score combining the weighted grade point average from the applicant's diploma supplement (35%), their research experience (30%), and a motivation interview (35%). Applicants must reach a minimum competitive score of 7.0 to be admitted.

This PhD program develops experts in computer science, information technology, and applied mathematics, with a focus on advanced research and innovation in areas like intelligent systems, big data, software development, and modeling. The curriculum includes core courses in research methods and scientific communication, along with electives covering machine learning, distributed systems, and computer vision. Students conduct independent research and present their work through a doctoral thesis. Graduates are prepared for leadership roles in academia, research centers, and industry.

This PhD program is open to candidates with a master's degree in computer science, information technology, mathematics, statistics, natural sciences, social sciences, or related fields. Applicants from certain backgrounds must also pass an entrance exam, and English proficiency at CEFR B2 level is required for studies in English. The program focuses on advanced research in areas like system analysis, intelligent systems, big data, mathematical modeling, and computer engineering. It prepares students for academic, research, and leadership roles in both industry and higher education.

Delivered jointly across three institutions, this doctoral program addresses informatics as a rapidly evolving field grounded in computational science and mathematical modelling, with a focus on artificial intelligence, data analysis, computational intelligence, and signal and image processing. It is aimed at individuals pursuing interdisciplinary research and innovative solutions that drive technological progress.

Core coursework covers the architectures of neural networks, methods for data analysis and visualization, heuristic algorithms, language technologies and information retrieval, mathematical models in informatics, algorithms for parallel and distributed computing along with their complexity analysis, and quantum algorithms. Alongside these subject-specific modules, students build core research competencies through a dedicated set of skills modules, including academic and technical research writing, design thinking in research, digital tools for research writing and publication, research data management, research ethics, grant management for research projects, science communication for public audiences, and systematic literature review methods.

Applicants must hold a master's degree or an equivalent higher education qualification in a field such as informatics, artificial intelligence, mathematics, informatics engineering, physics, mechanical engineering, or electrical and electronic engineering.

Admission is based on a weighted competition score combining the weighted grade point average from the applicant's diploma supplement (35%), their research experience (30%), and a motivation interview (35%). Applicants must reach a minimum competitive score of 8.0 to be admitted. As part of the broader application process, applicants are generally expected to submit materials such as a completed application specifying their preferred research topic, a CV, two letters of recommendation from researchers in the relevant field, evidence of prior scientific publications or an original research paper where publications are not available, a copy of a valid passport or identity document, and proof of payment of the application fee, and all applicants are required to attend an interview with the doctoral admissions committee.

This doctoral program is focused on advanced telecommunications engineering. It equips students for scientific, pedagogical, and innovative work in digital and electronic communications. Students can specialize in areas such as signal processing, microwave and quantum communications, photonics, mobile systems, and network design. The curriculum combines theoretical and practical courses with extensive research work, emphasizing independent problem-solving and presentation of results at international scientific forums. Graduates are expected to lead developments in telecommunications technologies and manage complex academic or industrial projects.

Applicants must hold a master's degree in engineering science with a focus on telecommunication technologies and network management, or an equivalent qualification.

This doctoral program in information technology engineering prepares students for independent scientific research and academic careers in IT sciences. It offers three sub-disciplines: computer control (technical and biosystems), systems analysis and design, and e-learning technology and management. Students complete courses in research methodology, scientific sub-fields, and foreign languages. Most of the workload is dedicated to research activities, with guidance from supervisors and participation in international collaborations. Graduates are expected to produce internationally recognized publications and a PhD thesis that contributes new knowledge or innovations to the field.

Applicants to this doctoral program must hold a master's degree in Engineering or Natural Sciences. Those from other academic backgrounds are required to pass an entrance exam to be eligible. A good command of English is essential, with a minimum score of 6.0 in IELTS, 547 in TOEFL (paper-based), or 76 in TOEFL iBT.

This PhD program prepares professionals to lead digital transformation in companies and institutions. It focuses on the study, development, and implementation of advanced digital technologies. The curriculum includes research methodologies, integrity, and electives like Data Analytics, Cybersecurity, and Robotics. Students must complete a thesis contributing original research to the field.

Applicants must hold a master's degree or equivalent, or a recognized foreign qualification aligned with the Bologna Process. Exceptionally, those with a relevant academic, scientific, or professional background may also be admitted. Candidates must have a background in Engineering or Science and Technology. Recognition of qualifications grants access to the PhD but does not imply degree equivalence.

This PhD program focuses on the development and management of e-learning technologies through interdisciplinary research in technology and education. It covers areas such as instructional media, educational data analytics, knowledge management, and cybersecurity in online learning environments. Students are trained to design, evaluate, and implement innovative e-learning solutions and to lead large-scale academic and industrial research projects. The program includes compulsory courses, electives, and extensive research work, aiming to prepare experts who can shape the future of digital education.

This PhD program is open to candidates with a master's degree in natural sciences or social sciences, or an equivalent qualification. An entrance exam is required, and English proficiency at CEFR B2 level is necessary for studies in English. The program focuses on interdisciplinary research in e-learning technologies, educational data analysis, instructional design, and digital knowledge management. Students develop skills to lead research, implement digital learning solutions, and contribute to innovation in educational systems and institutions.