University of Kansas

What you'll study

The programme combines advanced coursework with intensive original research. In the early years students complete core and elective courses to build depth and breadth across areas such as algorithms, machine learning, data science, databases, human–computer interaction, information retrieval, cybersecurity, distributed systems and formal methods. Typical advanced-level modules include:

• Advanced Algorithms and Complexity — analysis and design of algorithms, approximation and randomized methods.
• Machine Learning and Statistical Methods — supervised and unsupervised learning, probabilistic models and deep learning foundations.
• Databases and Information Management — data modelling, query processing and big data systems.
• Information Retrieval and Text Mining — indexing, search engines, evaluation metrics and natural language processing.
• Human–Computer Interaction — design, evaluation and user-centred methods for interactive systems.
• Computer and Network Security — cryptography, secure systems and privacy-preserving techniques.
• Distributed and Cloud Systems — concurrency, fault tolerance and systems architecture for scalable services.

Students participate in regular research seminars and journal clubs, complete a sequence of research rotations or supervised projects, pass a qualifying/comprehensive examination, and prepare and defend a dissertation that makes an original contribution to the field. Most students meet additional requirements such as teaching experience or professional development workshops.

Entry requirements

Applicants normally hold a relevant graduate degree (master’s) in computer science, information science, engineering or a closely related discipline, though exceptionally well-qualified candidates with a strong bachelor’s degree may be considered. Typical application components include:

• Academic transcripts demonstrating solid preparation in computing and mathematics.
• Letters of recommendation (usually three) from academic or professional referees who can speak to research potential.
• Statement of purpose describing research interests, relevant experience and proposed faculty mentors or research areas.
• Curriculum vitae highlighting research, publications, projects and relevant work experience.
• Evidence of English language proficiency for applicants whose first language is not English (accepted tests and minimum scores are listed by the University).

Standardised test requirements (such as the GRE) may vary; applicants should consult the programme pages or contact graduate admissions for current policy. Admission is competitive and funding is commonly offered to successful PhD applicants in the form of research or teaching assistantships.

Career prospects

Graduates of the PhD in Computer and Information Sciences pursue a broad range of careers. Typical paths include:

• Academic positions: tenure-track faculty and postdoctoral research roles at universities and research institutions.
• Research scientist/engineer roles: positions in industrial research labs and innovation teams at technology companies.
• Data science and machine learning leadership: senior roles in data analytics, AI engineering and product research.
• Specialised technical careers: cybersecurity expert, systems architect, database engineer or HCI researcher in industry or government.
• Public sector and non-profit research: applied research roles in government agencies, healthcare organisations and NGOs focused on information systems and digital infrastructure.

The programme’s emphasis on rigorous research methods, publication, and communication skills prepares graduates to lead research projects, secure external funding and translate research into deployed technologies.

Why study at University of Kansas

The University of Kansas offers a research-intensive environment with access to interdisciplinary collaborators across engineering, social sciences, medicine and libraries. Doctoral students benefit from close mentorship by faculty active in diverse areas of computing and information research, opportunities to publish and present work, and access to computing facilities and campus research centres.

The campus setting supports a balance of focused research and community engagement, with opportunities for teaching experience and professional development. Graduate students commonly receive financial support through research assistantships and teaching assistantships, enabling them to concentrate on research and training toward independent scholarship and leadership in computing and information sciences.