Clinical Research Informatics Postdoctoral (CRISP) Fellowship

The Clinical Research Informatics Postdoctoral (CRISP) Fellowship provides 1 or 2 years of tailored training for clinician investigators who seek to improve healthcare through the science of clinical research informatics. It is funded by a training grant (TL1-TR001871) from the National Center for Advancing Translational Science (NCATS), in conjunction with the UCSF Clinical and Translational Science Institute (CTSI) and the Department of Epidemiology and Biostatistics.

CRISP fellows obtain advanced didactic training in the methods of clinical research informatics and participate in regular work-in-progress and career development sessions. Fellows receive a stipend commensurate with their PGY/postdoctoral fellow status plus tuition assistance for didactic training. Applicant departments are responsible for covering approximately 40% of the total fellowship costs (see "Frequently asked questions" at the bottom of this page).

What is clinical research informatics?

Clinical Research Informatics, one of the five informatics specialties defined by the American Medical Informatics Society, involves using data science methods, analytics, and clinical practice observation to generate and disseminate knowledge related to health and healthcare delivery.

Careers in clinical research informatics may involve:

Selection, implementation, development, and maintenance of a technology ecosystem to support healthcare
- When should AI be implemented?
- How can we tell if AI improves health outcomes?
- What are the metrics?
Optimization of electronic health record (EHR) systems and data to support research administration, participant recruitment and consenting, data capture, intervention implementation, and other activities related to clinical research execution
Management and workflow of EHR data repositories, registries, marts, and warehouses, along with simplifying the process of leveraging these standardized repositories via reporting and analytics
Leveraging of EHR data for population health analytics and scientific inquiry
Use of implementation science methods and translation of research into evidence-based practice

Program

CRISP fellows receive in-depth training in clinical research informatics and data science through coursework in the Training in Clinical Research (TICR) program.

Conduct a mentored research project.
Attend weekly didactic sessions with UCSF (ACGME) Clinical Informatics Fellows.
Participate in regular work-in-progress sessions with the Learning Health Systems Embedded Scientist Training and Research Program.
Attend monthly Fellows Advancement Skills Training in Clinical Research (FAST-CaR) career development sessions.
Complete coursework: CRISP fellows who have not already received formal training in these areas will be encouraged to take additional courses [PDF].

Eligibility

The CRISP program is designed for clinical postdoctoral fellows with strong mentorship who are planning to submit a K award within two to three years. The CRISP program is open to all who meet academic, professional, and interest criteria. All applicants must meet the following criteria:

U.S. citizen or permanent resident
Doctoral degree in a healthcare profession
Clinical license in a healthcare profession (allopathic or osteopathic medicine, nursing, pharmacy, dentistry, psychology, physical therapy, acupuncture, podiatry)
Fewer than three years of prior funding through (institutional or individual) NRSA training grants

UCSF does not use race, gender, sex, or other protected categories or proxies for protected categories in the selection process.

Application Instructions

Selection Criteria

Selection criteria will focus on the candidate's potential to become a productive clinical investigator and successful K awardee as evaluated across five domains:

Mentorship. Experience of the mentor(s) and success of their prior trainees. Commitment of the proposed mentor(s) and plan for training.
Creativity of the candidate and potential to conduct innovative research based on background, areas of interest/expertise, prior publications, and grants.
Scientific strength, clinical importance, and feasibility of the proposed research plan.
Tangible resources provided by the mentor (e.g., workstation, computer, data analytic support, administrative support, travel to scientific conferences).
Academic Potential: Likelihood that the candidate will pursue an academic career as a clinical investigator whose work will have an important impact on health care.

Potential Mentors

CRISP Program Faculty Mentors and Domain Expertise
Mentor	Title and Relevant Roles	Domain Expertise for Mentorship Support
Julia Adler-Milstein, PhD	Professor of Medicine; Chief of the Division of Clinical Informatics & Digital Transformation (DoC-IT). Affiliated faculty in the Institute for Health Policy Studies	Use and uptake of EHR systems The use of AI and other digital tools in clinical settings
Rima Arnaout, MD	Assistant Professor in Medicine (Cardiology); member of the Bakar Computational Health Sciences Institute, and the Center for Intelligent Imaging	Precision phenotyping in biomedical imaging Deep learning using AI
Andrew Auerbach, MD, MPH	Professor of Medicine, MPI of the LHS E-STAR grant, and past Editor-In-Chief of the Journal of Hospital Medicine	Diagnostic errors Use and analysis of machine learning techniques for large volumes of clinical data
Yoshimi Fukuoka, RN, PhD	Professor of Physiological Nursing, CTSI mHealth research consultant, and prior Assistant Director for the CTSI Mentor Development Program	Generative artificial intelligence, with a particular focus on conversational agents (chatbots) Digital health interventions
Jin Ge, MD, MBA	Assistant Professor of Gastroenterology; affiliated faculty in the UCSF Bakar Computational Health Sciences Institute, and in the UCSF-UC Berkeley Joint Program in Computational Precision Health	Generative artificial intelligence Natural language processing Gastroenterology
Ralph Gonzales, MD, MSPH	Professor of Medicine, MPI of the LHS E-STAR grant, Associate Dean for Clinical Innovation, and Chief Innovation Officer for UCSF Health	Learning health systems Digital health innovations in care delivery Implementation science and sociotechnical theory
Ari Green, MD, MS	Professor of Neurology; Chief of the Division of Neuroimmunology and Glial Biology	Multiple sclerosis Validation of biomarkers and prediction models
Elaine Khoong, MD	Associate Professor of Internal Medicine and Clinical Informatics, Medical Director of Quality Improvement and Safety. Board certified in clinical informatics. LHS E-STAR faculty	Primary care Digital health interventions Implementation science in learning health systems Blood pressure management
Anobel Odisho, MD, MPH	Associate Professor of Urology, Epidemiology and Biostatistics, and Medical Director of Surgical Informatics	Computable phenotypes Natural language processing Large language models to analyze unstructured EHR data
Akinyemi Oni-Orisan, PharmD, PhD	Associate Professor, Clinical Pharmacy	Pharmacoepidemiology and pharmacogenomics Cardiovascular disease Precision medicine
Romain Pirracchio, MD, MPH, PhD	Prof. and Chief, Department of Anesthesia and Perioperative Medicine, Executive Member of UCSF-UC Berkeley Joint Program in Computational Precision Health	Applied research in Biostatistics and Artificial Intelligence Clinical research in Anesthesiology and Critical Care Medicine
Mark Pletcher, MD, MPH	Director, UCSF CTSI Informatics and Research Innovation; Chair of Dept. of Epidemiology and Biostatistics, affiliated faculty at Institute for Health Policy Studies	Consumer-facing data collection Digital health EHR-based clinical trial design and conduct (APeX-enabled Research [AER])
Lisa Rotenstein, MD, MBA	Assistant Professor of Medicine, Medical Director of Ambulatory Quality and Safety at UCSF Health, and Director of the Center to Advance Digital Physician Practice Transformation at UCSF (ADAPT)	Learning health systems Use of clinical AI tools Generative AI to improve healthcare
Vivek Rudrapatna, MD	Assistant Professor of Gastroenterology; Director of the UCSF Center for Real-World Evidence. Faculty, Bakar Computational Health Sciences Institute	Natural language processing Use of EHR data and large language models to identify clinical entities and inform clinical decision-making Use of real world data for clinical trial simulation and personalized medicine
Urmimala Sarkar, MD, MPH	Professor of Medicine, Director of the current NCATS KL2 program; MPI for UCSF CTSI NCATS K12 proposal. Co-Director of PrISM, an annual national symposium on social media research	Digital health design and evaluation Chronic disease management Community engagement
Gabriela Schmajuk, MD	Professor of Rheumatology, Section Chief for Rheumatology at the SFVA, co-director of the Quality and Informatics Lab	Health IT, EHR-enabled interventions Rheumatology Quality measurement National patient registries using EHR data
Marina Sirota, PhD	Professor of Pediatrics, Interim Director of the UCSF Bakar Center for Computational Science, faculty in the UCSF-UC Berkeley Joint Program in Computational Precision Health Program	Bioinformatics Computational biology Precision medicine
Neeta Thakur, MD, MPH	Associate Professor of Medicine and Pulmonary Critical Care	Geospatial analyses Complex data linkages Asthma Community engagement
Elizabeth Wick, MD	Professor of Surgery and Co-Chair of the research committee for the Department of Surgery	Automated data collection Use of large language models
Jinoos Yazdany, MD, MPH	Professor of Medicine and Rheumatology, Division Chief of Rheumatology, and Director of AI Monitoring at UCSF	Rheumatology AI monitoring, learning health systems Quality measurement

Fellows

Program Directors

Frequently Asked Questions

In accordance with Federal and State law and University policy, the University of California does not discriminate on the basis of age, gender, race, ethnicity, national origin, religion, sexual orientation, gender identity, health, or disability. For detailed information, please visit the Office for the Prevention of Harassment and Discrimination.

Clinical Research Informatics Postdoctoral (CRISP) Fellowship

What is clinical research informatics?

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Clinical Research Informatics Postdoctoral (CRISP) Fellowship

What is clinical research informatics?

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