Indiana University Bloomington

What you'll study

The programme combines rigorous coursework with sustained original research. Early-stage students typically take advanced courses to build depth in core areas—algorithms and theory, machine learning and AI, databases and data management, systems and networking, software engineering, cybersecurity, and human–computer interaction—alongside seminars in information science topics such as information behaviour, information retrieval, and socio-technical systems.

• Core and elective coursework to establish breadth and depth in chosen specialisms
• Research methods and statistics for computational and information science research
• Specialised seminars and reading courses tailored to dissertation topics
• Qualifying/Comprehensive examinations to assess readiness for independent research
• Original dissertation research under the supervision of a faculty advisor
• Opportunities for interdisciplinary collaboration with centres in data science, HCI, networks, and policy
• Teaching or mentoring experience through graduate assistantships

Entry requirements

Successful applicants typically hold a strong undergraduate degree in computer science, informatics, information science, engineering, mathematics or a closely related field; many applicants also hold a relevant master's degree. Admissions committees look for demonstrated academic achievement, relevant research experience (for example, publications, research assistantships, or substantial project work), and a clear statement of research interests that aligns with faculty expertise.

• Transcripts showing a high level of performance in quantitative and computing coursework
• A statement of purpose outlining research goals and potential faculty mentors
• Three academic or professional letters of recommendation that can speak to research potential
• A CV detailing research, publications, internships and technical skills
• Evidence of prior research experience is strongly preferred; a master’s degree can strengthen an application but is not always mandatory for exceptional candidates
• International applicants must meet the university's English proficiency requirements

Career prospects

Graduates of this PhD programme pursue diverse careers in academia and industry. Typical paths include tenure-track faculty positions, research scientist or engineer roles in industrial R&D labs, data science and machine learning positions in private sector organisations, and specialised roles in cybersecurity, software architecture, systems design and human-centred computing. Alumni also work in government research organisations, non-profit research institutes, and technology startups where advanced research skills are valued.

Why study at Indiana University Bloomington

Indiana University Bloomington offers this doctoral training through its Luddy School of Informatics, Computing, and Engineering, which brings together computer science, informatics and information science faculty. Students benefit from a collaborative, interdisciplinary environment with access to research centres and institutes focused on data science, human–computer interaction, networks and security. The university provides strong computing resources, opportunities for external partnerships, and a culture that supports publication and conference participation. Bloomington itself is a research-active campus with opportunities for cross-disciplinary work across social sciences, informatics, and engineering.