Postdoctoral Training Program - Center for Molecular Epidemiology
The Center for Molecular Epidemiology at the Geisel School of Medicine at Dartmouth invites applications for a postdoctoral fellowship designed to cross-train scientists in the fields of epidemiology, bioinformatics, biostatistics and health data science. The Center for Molecular Epidemiology is funded by an Institutional Development Award (IDeA) from the National Institutes of General Medical Sciences, that aims to apply state-of-the-art scientific discoveries and technologies to address major health concerns, explore common pathways of disease etiology and progression, and identify early indicators of disease pathogenesis.
Trainees have the opportunity to work with faculty members in the Center for Molecular Epidemiology with diverse research focuses related to molecular biomarkers, genomics, metabolomics, environmental exposures, cancer, human microbiome, pregnancy and children’s health outcomes, among others. Proficiency in R, SAS, or Stata is required, and experience analyzing high-dimensional data is desired. Quantitative research projects involve application and/or development of statistical methods for data generated from biospecimens collected as part of several large clinical trials and population-based cohort studies lead by investigators at the Geisel School of Medicine, Dartmouth-Hitchcock Medical Center, Norris Cotton Cancer Center, and Children’s Environmental Health and Disease Prevention Research Center.
Requirements
Applicants must possess, or be close to completing, a doctoral (PhD, MD, or MD/PhD) degree with graduate-level training related to the quantitative biomedical sciences, such as epidemiology, biostatistics, bioinformatics, or computational biology. Applicants with doctorates in basic sciences or clinical medicine with strong backgrounds in statistics or statistical programming are also encouraged to apply. Candidates are appointed for at least 2 years with an opportunity to extend to 3 years pending mutual interest and availability of funds. The starting date for the appointment will be negotiated between the primary mentor and candidate.
Application
Submissions should include a letter describing the background and interests of the applicant, curriculum vitae, and names and contact information for three references. Review of applications will commence immediately and will continue until positions are filled.
Applicant materials should be e-mailed to Vicki.Sayarath@dartmouth.edu
Geisel School of Medicine is an equal opportunity/affirmative action employer with a strong commitment to diversity. In that spirit, we are particularly interested in receiving applications from a broad spectrum of people, including women, persons of color, persons with disabilities, veterans or any other legally protected group.
Postdoctoral Training Program - Quantitative Population Sciences in Cancer
The Geisel School of Medicine at Dartmouth invites applications for a postdoctoral training and career development program designed to cross-train scientists in the fields of bioinformatics, biostatistics and epidemiology for cancer research in the biomedical sciences. The Training Program for Quantitative Population Sciences in Cancer at Dartmouth is supported by the Cancer Education and Career Development program of the National Cancer Institute. Trainees with doctorates in diverse biomedical sciences will choose a secondary focus area among the three core disciplines and participate in a combination of structured, group learning activities and individually designed mentored research opportunities. Stipends, course tuition and certificates of training are provided.
Requirements
Applicants must possess a PhD, combination PhD/MD, or MD degree. Applicants with a PhD in one of the three core disciplines (bioinformatics, biostatistics and epidemiology) are encouraged to apply for the purpose of receiving training in one of the other two disciplines. Highly qualified applicants with doctoral degrees in other biomedical sciences or in clinical medicine are also eligible and are encouraged to apply. Candidates who are current or former PIs on NIH Small Grants (R03s) or Exploratory/ Developmental Grants (R21s) are eligible. Individuals appointed to the program must be citizens or non-citizen nationals of the United States (U.S.), or must have been lawfully admitted to the U.S. for permanent residence. Individuals on temporary visas are not eligible. Candidates are appointed for at least 2 years and can be supported for up to 3 years. PIs in the program lead research efforts in lifecourse epidemiology, molecular epidemiology, biostatistical and bioinformatics methods development, interventional studies, medical bioinformatics, genomics, epigenomics, microbiome, and genome-wide association studies.
Application
Submissions should include a letter describing the background and interests of the applicant, curriculum vitae, and names and contact information for three references.
Applicant materials should be e-mailed to:
Vicki.Sayarath@Dartmouth.edu
Geisel School of Medicine is an equal opportunity/affirmative action employer with a strong commitment to diversity. In that spirit, we are particularly interested in receiving applications from a broad spectrum of people, including women, persons of color, persons with disabilities, veterans or any other legally protected group.
The following internal funding opportunities are available for students and postdocs affiliated with the department:
Department of Epidemiology Trainee Travel Award
To promote our education and training mission, funds for travel to scientific conferences will be awarded to one student/postdoctoral fellow per term of $1,000.00 each. Priority will be given to QBS PhD students and those who have not previously received this award. Deadlines will be October 1, December 15, and April 1.
Application Instructions
To be considered for an award, applicants must:
- Be a student or postdoctoral fellow mentored or co-mentored by a faculty member holding a primary or secondary appointment in the Department of Epidemiology
- Submit an abstract for a scientific conference as the presenter of the abstract.
- Provide a brief letter of recommendation from their mentor that describes the quality and impact of their work.
Contact Claire Weaver (Claire.V.Weaver@Dartmouth.edu) to apply.
Burroughs Wellcome Fund Program
The Dartmouth Big Data in the Life Sciences Training Program aims to develop a cadre of researchers engaging in true synergistic collaboration between quantitative and basic biomedical sciences.The program provides support for select students enrolled in any of the biomedical sciences graduate programs at Dartmouth. Selection into this competitive program is through application prior to the 2nd year of matriculation. The program provides student tuition and stipend support, as well as opportunities for computational resources and travel. Students or mentors interested in learning more about the program should contact Drs. Whitfield (Michael.L.Whitfield@Dartmouth.edu) or Christensen (Brock.C.Christensen@dartmouth.edu). For more information see the QBS website.
QBS T32 Training Program
The QBS T32 training program selects two highly qualified QBS predoctoral students each year for two years of support based on academic qualifications and a dissertation project that will focus on big data. The predoctoral trainees will complete an eight course core curriculum that will include two courses in computer science or data science, two courses in bioinformatics, two courses in biostatistics, two courses in epidemiology and a two course sequence in integrative biomedical sciences that exposes students to interdisciplinary research and that culminates in a collaborative big data class project. Students in this program take two elective courses, one term of teaching, journal clubs and seminars, training in responsible conduct of research, a written and oral qualifier exam, a yearly research in progress seminar, and the completion of a significant research project that forms the foundation of the written dissertation that is orally defended. For more information, contact Dr. Tor Tosteson (tor.d.tosteson@dartmouth.edu).