Florida State University

What you'll study

The programme emphasises original research grounded in a broad foundation of advanced coursework. Typical first-year study includes core topics such as advanced algorithms, operating systems, machine learning, and research methodology, followed by specialised coursework aligned with the students research focus.

• Research specialisms: artificial intelligence and machine learning, data science and databases, cybersecurity and privacy, computer vision and robotics, human-centred computing and information behaviour, high-performance and distributed systems, networking, and theoretical computer science.
• Programme structure: formal coursework and seminars, qualifying or comprehensive examinations, a research proposal or candidacy milestone, and completion of a doctoral dissertation that contributes new knowledge to the field.
• Typical modules and topics: advanced machine learning, statistical and computational learning theory, deep learning, information retrieval, privacy-preserving computation, secure systems engineering, advanced databases, natural language processing, visual computing, parallel and distributed computing, and research ethics and methods.
• Skills developed: independent research design, scholarly writing and presentation, advanced programming and systems development, data analysis and modelling, grant-writing and leadership through teaching or assistantship roles.
• Research environment: students work closely with faculty advisors, participate in research groups and labs, and collaborate with interdisciplinary centres on campus and external partners.

Entry requirements

Admission is competitive and evaluated on academic preparation, research potential and fit with faculty expertise. Applicants normally present one of the following:

• A relevant masters degree in computer science, information science, or a closely related discipline; applicants with an outstanding bachelors degree and strong research experience may also be considered.
• Transcripts demonstrating strong performance in core computing and mathematics courses (for example, algorithms, data structures, discrete mathematics, probability and statistics, and linear algebra).
• Research experience or publications are highly desirable; applicants should submit a statement of research interests outlining proposed areas of study and alignment with department faculty.
• Curriculum vitae, academic references (usually two or three), and representative writing or code samples where applicable.
• Proof of English proficiency for international applicants, as required by the university (accepted tests and minimum scores are listed by the university admissions office).

Some applicants may be asked to attend interviews with potential advisors. Standardised tests such as the GRE may be optional or considered on a programme-by-programme basis; consult the department for current testing policy.

Career prospects

Graduates of the PhD programme pursue a range of careers in academia, industry and government. Typical pathways include:

• University faculty positions and postdoctoral research roles, leading independent research and teaching in computing and information disciplines.
• Research scientist or research engineer roles in industrial labs and R&D teams at technology companies focused on machine learning, systems, security, or data-driven products.
• Senior technical and leadership positions such as principal engineer, data science lead, or chief technology officer in start-ups and established firms.
• Research and technical roles in government agencies, national laboratories and defence-related organisations working on cybersecurity, analytics, and critical infrastructure.
• Consultancy and specialist roles applying advanced computational methods to sectors such as healthcare, finance, transportation and energy.

Why study at Florida State University

Florida State University offers a collaborative research environment with active faculty across computer science and information science who supervise PhD projects spanning theoretical and applied work. The university hosts interdisciplinary centres and initiatives that support computing research, including strengths in cybersecurity and high-performance computing, which provide resources and collaboration opportunities.

Students benefit from access to on-campus research facilities, computing infrastructure, and partnerships with local industry and government organisations, as well as opportunities to teach and gain professional mentorship. The departmental community emphasises close advisor relationships, regular seminars and conferences, and a pathway to both academic and industry careers in advanced computing.