Delft University of Technology

What you'll study

The MSc Computer Science is a flexible programme combining compulsory core material, a choice of specialisation tracks, elective courses and an individual research project or thesis. Students develop advanced theoretical foundations and practical skills across software engineering, algorithms, machine learning, systems and human-centred computing.

• Core modules: advanced algorithms and complexity, formal methods and verification, concurrent and distributed systems, and computer architecture or operating systems topics depending on the track.
• Specialisations / tracks: typical options include Software Engineering & Trustworthy Systems, Data Science & Knowledge Engineering, Embedded and Networked Systems, Cyber-Physical Systems, Algorithms & Complexity, and Human-Computer Interaction. Each track groups focused electives and project opportunities.
• Electives: students choose from machine learning, deep learning, optimisation, natural language processing, computer vision, security and privacy, cloud and distributed computing, database systems, and specialised seminars offered by research groups.
• Project and thesis: a substantial individual research or design project supervised by academic staff, often conducted in collaboration with one of Delft’s research groups or external industry partners. Projects emphasise experimental evaluation, reproducible research and transfer to practice.
• Teaching format: lectures, advanced seminars, lab work, programming assignments, and group project work. Assessment is by written exams, project deliverables, presentations and the final thesis.

Entry requirements

Applicants are normally expected to hold a relevant bachelor’s degree in computer science, software engineering, information technology, mathematics, or an equivalent programme with a strong quantitative component. Candidates should demonstrate proficiency in programming, discrete mathematics, algorithms and basic software engineering concepts.

• Academic background: a recognised undergraduate degree with substantial computer science content. Where background is incomplete, the faculty may require additional preparatory courses.
• English language: proof of academic-level English proficiency is required for applicants whose prior education was not in English; accepted tests and minimum scores follow the university’s standard requirements.
• Supporting documents: academic transcripts, a statement of purpose describing research or study interests, and letters of recommendation are typically required. A CV and examples of prior projects or code can strengthen an application.
• Additional routes: outstanding candidates from other quantitative disciplines may be considered if they demonstrate relevant coursework and programming experience; bridging modules could be prescribed.

Career prospects

Graduates of the MSc Computer Science pursue technical and research-oriented careers in industry, government and academia. The programme prepares students for roles that require strong analytical skills, software craftsmanship and system design capabilities.

• Industry roles: software engineer, machine learning engineer, data scientist, systems architect, DevOps or cloud engineer, security engineer, and embedded systems developer.
• Research and development: R&D engineer in technology firms, research scientist in industrial labs, or continuation to a PhD for academic research careers.
• Specialist and leadership tracks: technical lead, product engineer for high-tech companies, or consultant in digital transformation and AI-driven projects.
• Employers: graduates work in multinational tech firms, startups, research institutes, and specialised engineering consultancies across domains such as AI, telecommunications, automotive and energy.

Why study at Delft University of Technology

Delft University of Technology offers a strong combination of high-quality teaching, active research groups and close ties with industry. The faculty’s research spans theoretical computer science to applied systems and human-centred computing, providing diverse supervision and project possibilities.

• Research-led teaching: courses are taught by researchers engaged in current topics, enabling students to work on cutting-edge problems and access modern lab facilities.
• Industry links: collaboration with technology companies, research institutes and the nearby high-tech ecosystem creates opportunities for internships, project partnerships and knowledge transfer.
• Facilities and community: access to well-equipped computing labs, high-performance computing resources, and an international student community that fosters interdisciplinary collaboration.
• Preparation for impact: the programme emphasises rigorous foundations, reproducible research practice and transferable skills, preparing graduates for both innovative industry roles and academic careers.