Computational medicine in the Heart: Integrated training Program
(CHIP) T32 Program
Cardiovascular (CV) disease is a major cause of mortality and morbidity, for which there is an urgent need for improved mechanistic understanding, and translation to novel diagnostic and therapeutic strategies. Computational medicine is poised to enable major breakthroughs by combining the life sciences with engineering, mathematical and computational tools including physics-based models and machine learning.
CHIP T32 provides comprehensive, structured training for post MD, PhD or MD/PhD fellows in computational medicine that address several unmet needs outlined by the National Research Council, NHLBI, academia and industry.
CHIP provides 2 years of structured training for a total of 6 fellows, who select mentors from thirty-eight diverse faculty with a rich track record of training. Faculty span numerous departments in the Schools of Medicine, Engineering and Humanities and Sciences. Training comprises interdisciplinary research, tailored coursework, professional development, and team-based activities. Fellows will learn in a rich environment including fellows at multiple levels of training. Programming is individualized, and courses are selected from offerings provided by the Cardiovascular Institute (CVI), Institute for Computational and Mathematical Engineering (ICME), center for Artificial intelligence in Medicine and Imaging (AIMI) and broadly within the Schools of Medicine, Engineering, and Humanities and Sciences.
Research and Career Advice
— Trainees meet quarterly with CHIP T32 directors and their Mentorship committee of 2-4 interdisciplinary faculty for feedback on their projects and career goals as well as discussions about topics relevant to academic research and professional development.
— CHIP T32 trainees have prioritized access to mentors in the CVI Trainee Mentorship Program, and from the ICME, to build their network.
— Short presentations at the Annual CVI Trainee Review Meeting and ICME symposia provide the trainees with feedback on their research and career trajectory from their peers and senior CVI scientists.
Conferences and Invited Talks
— Typically between $1000 and $3000 per year is available for conference- and training-related expenses. The exact number varies depending on the details of your appointment.
— Trainees are invited to present at CVI's Research Roundtable Series and ICME research symposia.
— Trainees are also invited to participate in the Early Career Symposium and other postdoctoral symposia of CVI and ICME.
— Trainees may request grant and manuscript feedback and support from CVI staff, as well as write-ups of their publications for CVI's website.
— As members of CVI, CHIP T32 trainees are eligible for CVI's Manuscript and Travel Awards.
— Compensation: The expected base pay for this position is the Stanford University required minimum for all postdoctoral scholars appointed through the Office of Postdoctoral Affairs. The FY23 minimum is $68,238. The pay offered to the selected candidate may be determined based on factors including (but not limited to) the qualifications of the selected candidate, budget availability, and internal equity.
Application deadline: May 15, 2023
If you are interested in applying for two-year research opportunities:
(1) Check to make sure you meet the following eligibility requirements (as per NIH policy) listed below:
— You must be a US citizen or permanent resident;
— You must not have already received more than two years of post-doctoral funding from NIH training grants (e.g., T32, NRSA) in order to be eligible for this award;
— You must have a PhD, MD, or equivalent degree by the start of training.
(2) Please identify and contact a faculty mentor to ensure that he or she has space in the lab, and that there is mutual interest in a training opportunity. Additional Stanford faculty members may also act as mentors in our program. Please indicate in your application who you would like to act as your primary research mentor.
(3) Fill out the online application. Please include all information and uploads during your application. Materials required: CV, brief statement of research goals and interests.