University of Chicago

What you'll study

This PhD is research-led and organised around the integration of medical visual communication and informatics methods. Core areas of study typically include medical image analysis; 3D modelling and animation for anatomy and physiology; information design and visual cognition; database design and biomedical ontologies; clinical data mining and machine learning; human–computer interaction and usability in clinical settings; and software engineering for healthcare applications.

Students follow a combination of coursework and independent research. Early-stage modules commonly cover advanced anatomy and physiology for visualisers, programming for scientists (Python, R), statistical methods for informatics, data visualisation principles, and clinical data standards (HL7, FHIR). Later-stage study focuses on specialised electives and a supervised research project leading to a doctoral dissertation. Practical work includes creating illustrative media, prototyping interactive visual analytics tools, applying machine learning to imaging or electronic health record (EHR) datasets, and user testing with clinicians and patients.

• Medical image processing and segmentation
• 3D modelling, animation and virtual/augmented reality
• Data visualisation theory and practice
• Clinical informatics, EHR data structures and standards
• Machine learning for biomedical data
• Human factors, usability testing and participatory design
• Research methods, ethics and reproducibility in biomedical research

Entry requirements

Applicants should hold a strong honours degree or a relevant master's degree in a related discipline such as biomedical sciences, computer science, data science, medical illustration/visual communication, biomedical engineering or a closely related field. Typical applicants demonstrate a combination of biological/clinical knowledge and computational or visualisation skills.

Admissions commonly expect:

• Academic transcripts showing strong performance in relevant undergraduate or postgraduate study.
• A statement of research interests outlining a feasible PhD proposal and how it aligns with faculty expertise.
• Evidence of practical skills — this may include a portfolio of illustration or visualisation work for candidates from visual disciplines, or code repositories and project descriptions for computational applicants.
• Two or three academic references commenting on research potential and subject competence.
• Where applicable, proof of English language proficiency at the level required by the university.

Successful applicants are typically those who can demonstrate interdisciplinary potential, prior research experience or relevant professional practice, and clear alignment with available supervisors and research groups within the university's medical, computational and visualisation units.

Career prospects

Graduates of this PhD programme pursue a wide range of careers at the intersection of healthcare, technology and communication. Typical pathways include roles in academia and research (postdoctoral positions, faculty), clinical informatics and digital health teams within hospitals, and product or research positions in medical technology companies developing imaging, diagnostic or visual analytics tools.

Other career destinations include scientific and medical illustration studios, health-focused design consultancies, pharmaceutical and biotechnology companies (visual communication and data analytics teams), museums and science centres (exhibition design and public engagement), and startups building clinical visualisation or decision-support platforms. Graduates are also well placed for roles in regulatory and standards organisations concerned with clinical data representation and interoperability.

Why study at University of Chicago

The University of Chicago offers a highly interdisciplinary research environment with close ties between the Pritzker School of Medicine, the Computation Institute and clinical partners at UChicago Medicine. Students benefit from access to clinical datasets, advanced imaging facilities, and collaborative labs that span informatics, computer science and biomedical visualisation.

The university is known for rigorous research training and a strong emphasis on methodological depth, critical thinking and reproducibility. PhD candidates can draw on expertise across departments, participate in cross-disciplinary seminars and collaborate with clinician–scientists, ensuring projects are both technically robust and clinically relevant. The environment supports entrepreneurial activity and translation of research into clinical tools and commercial products where appropriate.