We are seeking to hire a postdoctoral associate to join the Udler Lab in Diabetes Genetics Research Group, which spans the Massachusetts General Hospital (MGH) and the Broad Institute. We are an interdisciplinary team of clinicians, biostatisticians, and computational biologists who are working together to investigate the heterogeneity of type 2 diabetes with an unprecedented set of genetic data linked to clinical data in massive biobanks and study cohorts.

The ideal candidate will be passionate about learning and applying cutting-edge techniques in the burgeoning field of "precision medicine" and be motivated to publish research that significantly impacts how genomics is used to understand or treat diabetes. Projects may involve employing polygenic scores for diabetes, analyzing exome data to identify pathogenic variants, analyzing multi-omics datasets, or applying machine learning approaches to identify subtypes of diabetes. The successful candidate will demonstrate innovative and analytical thinking, will have outstanding academic records, an excellent technical background, strong communication skills, and will enjoy working in an interdisciplinary team. Applicants must have a PhD in a life-science or quantitative field.

We provide a vibrant research environment with close links to top academic institutions across the Boston area and provide the potential for your contributions to be recognized worldwide. The Udler Lab spans the MGH, a world-class academic medical center, and the Broad Institute in Cambridge, which serves as a hub for the Harvard and MIT biomedical communities. These resources provide an unparalleled opportunity for a motivated postdoc to grow professionally and achieve high impact science, set alongside all of the cultural and natural benefits of the broader Boston metropolitan area.

* The overarching goal of the postdoctoral research project will be to leverage multimodal biological datasets to understand heterogeneity of diabetes.

* Apply cutting-edge computational, mathematical, and statistical methods and algorithms to identify subtypes of diabetes.

* Work closely with a multidisciplinary team to analyze large genomic and multi-omic data sets.

* Critically review, summarize, and communicate results.

* Present work at scientific meetings and write up findings for publication.

* PhD in genetics, biology, bioinformatics, or a closely related field, with solid training in analytical methods.

* Computational/programming and analytical skills.

* Fast learner and analytical thinker, comfortable taking initiative to learn new skills and drive projects to completion.

* Experience with analyzing biological data (including next-generation sequencing data) in a research setting is strongly preferred.

* Proficiency with R and experience in Unix/Linux environments (including shell scripting) is preferred.

• Demonstrated capability as highly organized, a creative problem-solver, detail-oriented, self-motivated, and able to work independently as well as within cross-functional teams.
• Strong communication and writing skills.