Dartmouth College

What you'll study

The PhD in Computer Science is centred on sustained, original research guided by faculty mentors, supported by coursework and departmental seminars. Typical study begins with advanced coursework to build depth and breadth across core areas—algorithms and theory, machine learning and data science, systems and networking, programming languages and software engineering, human-computer interaction, security and privacy, graphics and computational biology. Students also take research seminars, reading courses and practical lab rotations to identify a thesis topic.

Programme structure commonly includes:

• Initial coursework and breadth requirements to ensure mastery of foundational topics.
• Qualifying examinations or milestone assessments that evaluate readiness for independent research.
• Selection of a research advisor and formation of a dissertation committee.
• Original research culminating in a written dissertation and public defence.
• Teaching or mentoring responsibilities, which provide pedagogical experience.

Examples of modules and subject areas you can expect to encounter: advanced algorithms, probabilistic modelling and optimisation, deep and statistical machine learning, distributed systems, operating systems, computer networks, programming languages, compilers, software engineering, human-centred computing, security engineering, computational biology and bioinformatics, graphics and vision, and specialised seminars on emerging topics. Independent study and research credits form the bulk of later-stage doctoral work.

Entry requirements

Applicants are expected to hold a strong undergraduate degree in computer science, electrical engineering, mathematics or a closely related discipline; many successful applicants have a master's degree or prior research experience. Key requirements and favourable qualifications include:

• Strong academic record demonstrating proficiency in core areas such as discrete mathematics, linear algebra, probability and data structures/algorithms.
• Demonstrable programming experience and familiarity with software development practices.
• Evidence of research potential—this can be prior publications, research projects, summer research experiences or a master’s thesis.
• Three academic or professional letters of recommendation addressing research promise and technical ability.
• A clear statement of purpose outlining research interests and fit with Dartmouth faculty; a CV summarising research and technical experience.
• For applicants whose first language is not English, standardised English language test scores may be required; consult the department for current expectations.

Admissions committees evaluate fit with faculty interests and the capacity for independent, sustained research. Standardised test policies and precise documentation requirements are set by the department and may change; applicants should consult the department’s admissions page for up-to-date instructions.

Career prospects

Graduates of the PhD programme pursue a range of careers where deep technical expertise and research leadership are prized. Common pathways include:

• Academic positions as tenure-track faculty or postdoctoral researchers in computer science and related departments.
• Research scientist or research engineer roles in industrial research labs (for example in technology companies and specialised R&D organisations).
• Technical leadership roles in product teams, machine learning engineering, data science, systems architecture, cybersecurity and software engineering at established companies or startups.
• Positions in government and national laboratories applying advanced computing to scientific and engineering challenges.

The programme’s emphasis on both foundational theory and applied systems equips graduates to move between academia and industry, to found or join startups, or to take leadership roles in interdisciplinary research.

Why study at Dartmouth College

Dartmouth offers a PhD experience characterised by a small, tightly knit computer science community with high faculty access and close mentorship. The department fosters interdisciplinary collaboration across the College and with professional schools, including ties to engineering, medicine, business and the Neukom Institute for Computational Science. Students benefit from opportunities to work with faculty on cutting‑edge projects, participate in collaborative labs and access resources typical of a research university while enjoying a personal, collegial environment.

Additional advantages include teaching and mentoring experience with undergraduates, cross-disciplinary course offerings, and close connections to regional and national research networks. Prospective students who value personalised mentorship and interdisciplinary applied research will find Dartmouth’s environment particularly supportive for launching a research career.