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 (RO3s) 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 with the possibility to take courses or receiving funding towards an MS degree through Quantitative Biomedical Sciences Graduate program at Dartmouth. PIs in the program lead research efforts in lifecourse epidemiology, molecular epidemiology, biostatistical and bioinformatics methods development, statistical network analysis, clinical trial design, longitudinal with intensive monitoring, statistical imaging, biomedical informatics, genomics, epigenomics, microbiome, and genome-wide association studies.
The Geisel School of Medicine at Dartmouth is an academic institution located in Lebanon and Hanover, New Hampshire, in the Upper Connecticut River Valley, with easy access to New England mountains, lakes, and coastal regions. Home to community offering excellent schools, lively arts, and unmatched quality of life in a beautiful, rural setting.
Submissions should include a letter describing the background and interests of the candidate, curriculum vitae, and names and contact information for three references.
Applicant materials should be emailed to: QPSC@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.
Position Qualifications: Candidates should have a Ph.D. or equivalent degree in epidemiology, cancer biology, biostatistics, bioinformatics, or a closely related field. Critical to this position is the ability to conduct independent research and work cooperatively as part of a research team.projects include investigations on epigenetics and cell heterogeneity in cancer, with opportunities to work within specialized collaborative groups in the immunomethylomics area.Excellent oral and written communication skills are essential. The candidate should also have quantitative training and strong computational skills. Proficiency in R is critical, and experience using Python is desirable. Experience analyzing DNA methylation microarray data, and RNAseq (bulk and single-cell) data or other high-dimensional “omics” data is highly desirable.
Postdoctoral Research Opportunity in Environmental and Molecular Epidemiology
The Department of Epidemiology at the Geisel School of Medicine at Dartmouth is seeking
applications for a postdoctoral researcher in environmental and molecular epidemiology. Ongoing
projects include investigations on maternal and child health, environmental mixtures, and epigenetics,
with opportunities to work with several large population-based studies, including two pregnancy
cohorts.
Position Qualifications: Candidates should have a Ph.D. or equivalent degree in epidemiology,
environmental health, biostatistics, bioinformatics, or a closely related field. Critical to this position is
the ability to conduct independent research and work cooperatively as part of a research team.
Excellent oral and written communication skills are essential. The candidate should also have
quantitative training and strong computational skills. Proficiency in R is preferred. Experience
applying environmental mixture methods or experience analyzing next-generation sequencing data
(e.g., RNA-seq, WGBS) or other high-dimensional “omics” data is desirable but not required.
Training Opportunities: The successful candidate will work with a dedicated mentor in a supportive
and collaborative research environment. In addition to receiving training in environmental and
epigenetic epidemiology and manuscript and grant writing, the postdoctoral fellow will be encouraged
to attend the numerous career development seminars and workshops offered at Dartmouth, present
at scientific meetings and conferences, develop independent research projects, and apply for a
K99/R00 or other research grants.
Salary and Benefits: A competitive salary and benefits will be provided.
Application Information: Applications should include a 1-2 page letter describing the candidate’s
scientific interests and research background, a curriculum vitae, and the names and contact
information of three references. Review of applications will commence immediately and will continue
until the position is filled. Materials should be e-mailed to Dr. Caitlin Howe
(Caitlin.G.Howe@Dartmouth.edu).
Application Deadline: Open until filled.
The following internal funding opportunities are available for students and postdocs affiliated with the department:
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).