MULTIDISCIPLINARY TRAINING PROGRAM (T32) IN CARDIOVASCULAR EPIDEMIOLOGY
The Boston University Section of Preventive Medicine and Epidemiology is seeking candidates for its T32 Training Grant in Cardiovascular Epidemiology awarded by the National Heart, Lung, and Blood Institute. Trainees will focus their 2-year training on the epidemiology of cardiovascular disease such as coronary heart disease, stroke, heart failure and other forms of vascular disease, following one of the training pathways: statistical genetics and genomics, computational biology and bioinformatics, or clinical epidemiology.
Qualifications required
1) US Citizen or green card holder 2) a) Ph.D. degree in Biostatistics, Epidemiology, Computational Biology, Bioinformatics, Genetics and Genomics or related field and programming skills (SAS and/or R preferred) or b) MD degree
The successful candidate will participate in training activities including pathway-specific coursework and workshops, as well as individual professional development plan workshops, one-on-one professional counseling and career planning, grant writing workshops, research seminars, journal internships, and working on research projects with a Boston University senior investigator on longitudinal epidemiological studies such as Framingham Heart Study, Long Life Family Study and other cohort studies. All trainees will be supervised by their assigned faculty mentor as well as by the program’s co-directors for progress evaluation.
Interested candidates should send the following materials to CardioEpi@bu.edu:
- Cover letter indicating reason for applying to this training program
- Curriculum vitae
- 2 recommendation letters
Boston University is an equal opportunity employer. Under-represented minorities are strongly encouraged to apply. For more information, please contact:
- Ramachandran S. Vasan (vasan@bu.edu) or Vanessa Xanthakis (vanessax@bu.edu) if you are interested in the clinical epidemiology path
- Paola Sebastiani (sebas@bu.edu) if you are interested in the Statistical Genetics and Genomics or the Bioinformatics and Computational Biology path
