GENERAL SUMMARY/ OVERVIEW STATEMENT:
The Psychiatric and Neurodevelopmental Genetics Unit (PNGU), based in the Center for Genomic Medicine (CGM), and Department of Psychiatry at the Massachusetts General Hospital (Boston), is seeking highly motivated and enthusiastic candidates with expertise/interests in epigenetics for a post-doc opening to begin Spring 2022. Working with a multidisciplinary team under the direction of principal investigator Dr. Erin C. Dunn (www.thedunnlab.com) at MGH, applicants will contribute to an innovative project funded by the NIMH that focuses on integrating longitudinal data with insights from genetics, epigenetics, and human development to examine the developmental causes and consequences of DNA methylation (DNAm) on risk for depression in adolescence and young adulthood and time-dependent effects of protective factors on depressive symptom trajectories. Our overarching goal is to identify possible sensitive periods in development, or life stages when the brain is highly plastic and experience, including stress exposure, can impart more enduring effects on risk for depression. Our highly collaborative and dynamic research environment includes scientists and trainees at MGH, Harvard Medical School, and the Harvard T.H. Chan School of Public Health.
The new hire will be appointed as a Research Fellow at the Massachusetts General Hospital and Post-Doc at the Harvard Medical School.
The post-doc’s responsibilities will involve working with genetic and phenotypic data from a 20-year longitudinal study to perform epigenome-wide association analyses (EWAS) and implement several novel analytic methods, including: causal inference approaches, statistical mediation, and Mendelian Randomization. The post-doc will function as a high-level contributor, coordinator, and team member in this work, with numerous opportunities for interactions with investigators from across the world.
Candidates with backgrounds in multiple disciplines, including but not limited to epidemiology, genetics, and epigenetics are encouraged to apply. This is a highly unique opportunity for someone seeking an interdisciplinary experience to work with a large collection of epigenetic, genetic, and rich phenotypic data while receiving outstanding team-based mentorship. To apply, please send a single email containing your CV and a brief statement describing your qualifications for this position to Ms. Alison Hoffnagle, Program Director at ahoffnagle@mgh.harvard.edu.
PRINCIPAL DUTIES AND RESPONSIBILITIES:
- The Post-Doctoral Fellow will
- Contribute to the project’s work plan and timeline to accomplish the goals of the study
- Perform complex data acquisition, storage, cleaning, and pre-processing
- Perform advanced quantitative statistical analysis methods related to the study of sensitive periods for stress-induced DNAm signatures and subsequent depression risk
- Perform laboratory procedures to manipulate DNAm at promising CpG sites using CRISPR/Cas9, or oversee technicians/collaborators involved in performing procedures
- Disseminate results via conferences and journal publication
- Act as a statistical subject matter expert on sensitive periods, DNAm, and depression risk
The Post-Doctoral fellow will be situated in the MGH under the guidance and mentorship of Dr. Erin C. Dunn.
SKILLS & COMPETENCIES REQUIRED:
- The ideal candidate should have received (or expect to receive soon) a Ph.D. in Biology, Biochemistry, Epidemiology, Genetics, Genomics or other closely related fields.
- Evidence of a strong publication record, including first (or co-first) author of one or more peer-reviewed scientific publications
- Excellent English verbal and written communication skills
- Able to work both independently and in a team
- Advanced knowledge of statistical analysis approaches (e.g., linear and logistic regression; longitudinal analyses)
- Interest in the identification and validation of biomarkers of mental health risk
- Must be able to work independently as well as part of a team in a fast-paced, highly collaborative, and supportive environment
- Ability to adapt to shifting priorities in response to changing deadlines and the needs of the lab
- Excellent organizational skills
- Excellent quantitative and organizational skills
- Proven ability to work well in collaborative environment
- Ability to perform complex statistics or biostatistics, data mining, database management, and computer programming (e.g., SAS, R, Unix).
LICENSES, CERTIFICATIONS, and/or REGISTRATIONS: Not Applicable
EDUCATION: Doctoral Degree
Field of Study/Additional Specialized Training: Not Applicable
EXPERIENCE: Required: Recent PhD graduate
SUPERVISORY RESPONSIBILITY (authority to hire, promote, or terminate): Not Applicable
FISCAL RESPONSIBILITY: Not Applicable
WORKING CONDITIONS: TBD
EEO Statement