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Postdoctoral Research Fellow

Location
Boston, MA

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Postdoctoral Research Fellow
**MEMBERS ONLY**SIGN UP NOW***.
in
Boston
MA
USA
Compensation
$60,000 to $62,000 Annually
Benefits Offered
401K, Dental, Medical, Vision
Employment Type
Full-Time
Why Work Here?
“This position is suited to a person who is excited by the prospect of applying their quantitative analysis skills to cancer genomics”
The Carter lab at The **MEMBERS ONLY**SIGN UP NOW***. is seeking a talented and highly motivated post-doctoral fellow in population genetics to leverage our unique resource of painstakingly collected human cancer-tissue samples in order to elucidate mechanisms of cancer drug-resistance and metastasis. The Carter lab has pioneered the application of whole exome sequencing to characterize somatic genetic alterations in archival samples and to infer phylogenetic relationships between cancer subclones. We partner closely with the Brastianos lab at MGH to study genomic alterations in human brain metastasis patients, experimentally validate hypotheses in animal models, and translate findings to clinical trials. We recently received a 5-year NIH R01 grant to perform whole-exome sequencing on hundreds of brain metastases from lung adenocarcinoma. We anticipate that this dataset will nominate dozens of somatic metastasis drivers, which we will follow-up on with functional studies.
We are seeking a skilled quantitative geneticist to analyze data from brain metastases and unpaired primary tumors of the same histology, in a novel somatic case-control mutational burden analysis. The aim of this analysis is to optimally compute the evidence for increased positive-selection in the brain metastasis (case) vs. primary lung cancer (control) cohorts.
The fellow will be responsible for the development and optimization of novel statistical tools enabling calibrated genome-wide discovery of differential positive selection, while controlling for multiple confounding sources of variation, both at the sample level (e.g. exposure to mutational processes, germline and somatic mutation status), and at the genome level (e.g. early vs. late-replicating DNA, open vs. closed chromatin). Because accounting for mutational heterogeneity is so central to sensitive and specific detection of positive selection in cancer genomes, the fellow is expected to acquire expertise in DNA damage and repair, as well as processes that influence regional variation in somatic mutation rates observed in cancer genomes.
The fellow will join a strong and diverse team of computational biologists, clinical oncologists, technologists, experimental scientists, and software engineers and benefit from immersion in the scientific community at Harvard, Dana-Farber, MGH, and the Broad Institute. Successful candidates are expected to excel at critical thinking, be quick learners for new analytical approaches, and capable of applying or developing novel computational methods for solving complex problems. Candidates must have a doctoral degree, an excellent publication record, and great communication skills. The ideal candidate has a strong quantitative background and a demonstrated ability to tackle large, complex programming projects.
This position is suited to a person who is excited by the prospect of applying their quantitative genetics
skills to uncover key drivers of deadly metastatic cancer.
Roles and Responsibilities:
Develop algorithms for detecting positive selection in metastasis that advance the state-of-the-art
Implement and maintain robust analysis pipelines for detecting positive selection
Work with lab members to interpret the biological significance of findings, plan validation experiments,
and design follow-up studies
Publish new methods and results in academic journals and conferences
Present findings to internal and external multidisciplinary audiences in a clear and cohesive manner
Critically evaluate computational biology tools
Follow relevant scientific literature to ensure use of optimal methods and understand
emerging practices across the field, including evaluating newly developed methods
Support analysis by
biologist/clinician
colleagues without computational trainingMicrosoft Word - Post-doctoral fellow in clonal population genetics.doc
Regularly attend and present at lab and project team meetings to ensure continuous communication around methods and tools developers
Skills and Abilities:
A PhD in a quantitative field with a heavy programming component as well as a strong interest in population genetics as demonstrated by peer-reviewed publications
Experience with analysis of high-throughput DNA sequencing data is desirable
Strong demonstrated skill in statistical algorithm development
Independent, highly motivated, highly collaborative and works well with others
Excellent communication, organization, and time management skills
Company address:
3 Blackfan Circle, Boston MA 02115
Other applicants:
3
3
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