Postdoctoral Opportunities

Applicants are welcome to apply for more than one position, but a separate application will be required for each position.

Postdoctoral Research Position in Cancer Genomics
Postdoctoral Research Positions in Computational Biology and Metagenomics
Postdoctoral Research Position in Cancer Computational Biology and Bioinformatics
Postdoctoral Research Position in Statistical Methods for Implementation Science Research

 

Postdoctoral Research Position in Cancer Genomics

Description:

One postdoctoral position in cancer genomics are available at the Guo-Cheng Yuan Lab in the Department of Biostatistics and Computational Biology at Dana-Farber Cancer Institute/Harvard School of Public Health.

The goal of the Yuan Lab is to develop computational approaches to analyze and integrate genomic data with the aim to elucidate systems-level gene regulatory mechanisms in development and disease. Current projects include inference of gene regulatory networks, cancer genomics, genome-wide chromatin state characterization, functional characterization of genetic variants, and single-cell analysis. We closely collaborate with basic biologists and medical clinicians at the Harvard Medical School to gain mechanistic insights into the stem cell biology as well as cancer and lung diseases. Detailed description of our research can be found at our group website: http://bcb.dfci.harvard.edu/~gcyuan

The candidate will work closely collaborate with clinical investigators at Dana-Farber Cancer Institute to identify genetic and gene expression signatures of cancer subtypes, to investigate the mechanism for cancer progression and treatment response. The candidate will also develop computational methods for integrative analysis of gene expression, DNA sequence, and epigenomic data to construct and dissect gene regulatory networks, and/or to develop new single-cell analysis approaches.

Qualifications:

The successful applicant(s) should hold a doctoral degree or equivalent qualification in computational biology, (bio)statistics, computer science, or a similar field. Candidates holding a degree in biological/medical science are also welcome to apply if they have demonstrated experience in computational or statistical work. Strong programming (in Python, R, Matlab, or C/C++) and communication skills are required. Previous experience in analysis, interpretation, and integration of genomic data-types is required.

Lead author in at least one publication in major peer-reviewed scientific journals.

Additional Information:

Interested applicants please send CV and at least two recommendation letters to Dr. Guo-Cheng Yuan (gcyuan@jimmy.harvard.edu).

Harvard University seeks to find, develop, promote, and retain the world’s best scholars. Harvard is an Affirmative Action/Equal Opportunity Employer. Applications from women and minority candidates are strongly encouraged.

Information on resources for career development and work/life balance at HSPH can be found at: Career development and work/life balance.



Postdoctoral Research Positions in Computational Biology and Metagenomics

Description:

The Huttenhower lab in the Biostatistics Department of the Harvard School of Public Health is seeking to fill five bioinformatics postdoctoral research positions:

  • Computational methods development for biomolecular function and pathway analysis of metagenomes and metatranscriptomes. The successful candidate will build on the lab’s HUMAnN, ShortBRED, and PICRUSt methods for microbial community profiling to create the next generation of meta’omic metabolic reconstruction algorithms. Expertise in machine learning, Python development, and the Linux/Unix command line environment is required.
  • Statistical methods development for human transcriptomic and microbial metatranscriptomic RNA-seq high-dimensional data. The successful candidate must be statistically trained and familiar methods implementation in R/Bioconductor packages. He or she will work at the interface of biostatistics, bioinformatics, and cancer biology to develop novel analysis methods (diagnostic/prognostic biomarker discovery and outcome prediction) for meta’omic data in the context of molecular epidemiology of colorectal cancer.
  • Analysis of the gut microbiome in inflammatory bowel disease. The successful candidate will be appointed through the Broad Institute and will be responsible for analysis of primary microbiome samples (16S rRNA gene sequencing, shotgun metagenomics, and metatranscriptomics) and meta-analysis of studies from throughout the Crohn’s and Colitis Foundation of America Microbiome Initiative in order to prioritize candidate microbes and microbial biomolecules for experimental characterization. He or she will work closely with Drs. Ramnik Xavier and Dirk Gevers as part of the CCFA consortium.
  • Analysis of the human microbiome in colorectal cancer. The successful candidate will be appointed through the Broad Institute and will be responsible for executing a STARR Cancer Consortium-funded project investigating the gut microbiota’s role in modulating dietary and genetic (Lynch syndrome) colorectal tumorigenesis.
  • Analysis of multi’omic data describing the human microbiome in type 1 diabetes. The successful candidate will be appointed through the Broad Institute and co-advised jointly with Dr. Dirk Gevers’ lab, and he or she will be responsible for computational analysis of over 10,000 microbiome samples as part of the TEDDY (The Environmental Determinants of Diabetes in the Young) study.

The Huttenhower lab is broadly engaged in methods development for and multiple collaborative studies of the roles of the human microbiome in health and disease, with a focus on computational methods to characterize biomolecular functions within these microbial communities and their interactions with host immunity and genetics. The group works closely with the Broad Institute, the Dana-Farber Cancer Institute, and the broader Boston biomedical and life sciences communities, resulting in a rich environment for quantitative, computational, and laboratory collaborations.

Qualifications:

Doctoral degree in Computer Science, Statistics, Biostatistics, Bioinformatics, Biology, or a related field; proficiency in one or more statistical or scripting languages appropriate for scalable data analysis; comfort and experience with programming for biological data analysis; familiarity with functional genetic and/or genomic data, as indicated by publication record; ability to communicate scientific material and collaborate well.

Additional Information:

Please submit a cover letter (including a brief but detailed statement of interest), CV, and contact information for at least three references to Dr. Curtis Huttenhower at chuttenh@hsph.harvard.edu AND biostat_postdoc@hsph.harvard.edu.

Harvard University seeks to find, develop, promote, and retain the world’s best scholars. Harvard is an Affirmative Action/Equal Opportunity Employer. Applications from women and minority candidates are strongly encouraged.

Information on resources for career development and work/life balance at HSPH can be found at: Career development and work/life balance.



Postdoctoral Research Position in Cancer Computational Biology and Bioinformatics

Description:

The Department of Biostatistics and Computational Biology at the Dana-Farber Cancer Institute seeks a postdoctoral fellow with expertise in Cancer Computational Biology and Bioinformatics to work as part of an international, interdisciplinary team working on integrated analysis of genomic profiles in Breast Cancer in a large cohort study.

This postdoctoral fellow will work with Dr. Quackenbush to develop analytical methods for integrating the various data that will be collected as part of this project and will work with the various individual investigators on the analysis of their individual and collective data sets. Opportunities exist for the analysis of gene expression, GWAS, and other data and the development of new methods for linking and interpreting these data.

Qualifications:

Doctoral degree in Biostatistics and/or Computational Biology.

Additional Information:

Applicants should send a curriculum vitae and the names of three references to julianna@jimmy.harvard.edu, or to: PhD in Biostatistics Job Search, Attn: Julianna Coraccio, Dana-Farber Cancer Institute, 450 Brookline Ave. SM822, Boston MA 02215.

Consideration of an application will begin after the application package is complete.

Applications from minority and female candidates are especially encouraged. Dana-Farber Cancer Institute is an AA/EOE.



Postdoctoral Research Position in Statistical Methods for Implementation Science Research

Description:

Postdoctoral Research Fellow position in methods for implementation science research is available in the Department of Biostatistics with Dr. Donna Spiegelman. This position involves methodological developments and applied work aimed at the design and analysis of large-scale population-based studies to evaluate the effectiveness of interventions to improve health and prevent the development of diseases. Applications to the prevention of HIV/AIDS, of chronic disease, and in environmental health will motivate the statistical research.

Qualifications:

Qualifications are a PhD in statistics or biostatistics, strong programming skills, as well as good written and oral communication skills. Prior course work in epidemiology and/or experience with epidemiologic data preferred. Candidates whose doctoral dissertation focused on survival data analysis, causal inference, theoretical statistics, study design, and longitudinal models are most suitable for this position.

Additional Information:

Scientific questions regarding this position can be sent to Donna Spiegelman at stdls@hsph.harvard.edu. Applications will be considered as they arrive. To apply, send cover letter describing your research interests as it relates to this position, with CV and names of three references. Please be sure to indicate your qualifications in terms of each of the items mentioned above. In your application, please reference “Implementation Science Methods Postdoc”. Application materials should be sent by email (preferred) to biostat_postdoc@hsph.harvard.edu, or mail to: Postdoc Search, c/o Vickie Beaulieu, Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Building 2, 4th Floor, Boston MA 02115.

Harvard University seeks to find, develop, promote, and retain the world’s best scholars. Harvard is an Affirmative Action/Equal Opportunity Employer. Applications from women and minority candidates are strongly encouraged.

Information on resources for career development and work/life balance at HSPH can be found at: Career development and work/life balance.