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:

  • Diagram, venn diagramDescription automatically generatedSelection, 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.

  1. Conduct a mentored research project.
  2. Attend weekly didactic sessions with UCSF (ACGME) Clinical Informatics Fellows.
  3. Participate in regular work-in-progress sessions with the Learning Health Systems Embedded Scientist Training and Research Program.
  4. Attend monthly Fellows Advancement Skills Training in Clinical Research (FAST-CaR) career development sessions.
  5. 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. Applicants with backgrounds that are underrepresented in Medicine and candidates from the Schools of Nursing, Pharmacy, and Dentistry are especially encouraged to apply. 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
Application Instructions

Application

Approximate Timeline

Applications Due:             April 1, 2025
Offers Extended:              May 1, 2025
Fellowship Begins:           July 1, 2025
 

Blank Sample Application (PDF)

 

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:

  1. Mentorship. Experience of the mentor(s) and success of their prior trainees. Commitment of the proposed mentor(s) and plan for training.
  2. Creativity of the candidate and potential to conduct innovative research based on background, areas of interest/expertise, prior publications, and grants. 
  3. Scientific strength, clinical importance, and feasibility of the proposed research plan.
  4. Tangible resources provided by the mentor (e.g., workstation, computer, data analytic support, administrative support, travel to scientific conferences).
  5. 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
MentorTitle and Relevant RolesDomain Expertise for Mentorship Support
Julia Adler-Milstein, PhDProfessor 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, MDAssistant 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, MPHProfessor 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, PhDProfessor 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, MBAAssistant 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, MSPHProfessor 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, MSProfessor of Neurology; Chief of the Division of Neuroimmunology and Glial Biology
  • Multiple sclerosis
  • Validation of biomarkers and prediction models
Elaine Khoong, MDAssociate 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, MPHAssociate 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, PhDAssociate Professor, Clinical Pharmacy
  • Pharmacoepidemiology and pharmacogenomics
  • Cardiovascular disease
  • Precision medicine
Romain Pirracchio, MD, MPH, PhDProf. 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, MPHDirector, 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, MBAAssistant 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, MDAssistant 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, MPHProfessor 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, MDProfessor 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, PhDProfessor 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, MPHAssociate Professor of Medicine and Pulmonary Critical Care
  • Geospatial analyses
  • Complex data linkages
  • Asthma
  • Community engagement
Elizabeth Wick, MDProfessor 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, MPHProfessor 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 Director

CRISP is led by Mary Whooley, MD, UCSF Professor of Medicine, Epidemiology & Biostatistics ([email protected]). Administrative questions can be addressed to Christian Leiva ([email protected]).

Frequently Asked Questions