Bioinformatics/Computational Biology Postdoc - Single Cell and Spatial

The Vlachos Lab and the Spatial Technologies Unit are currently looking for talented postdoctoral researchers to lead large-scale spatial/single cell initiatives within our research program as well as to devise novel computational methods that will enable us to bring these two novel technologies closer to translation. The researcher will have the ability to leverage some of the most extensive single cell and spatial transcriptomic datasets to date, generated in-house.

The Vlachos lab is part of large scale initiatives, such as the Human Biomolecular Atlas Project (HuBMAP - enabling the postdoctoral researcher become an integral part of the single cell and spatial community.

Local and International Applicants are encouraged to apply

The Postdoc Single Cell and Spatial Technologies Bioinformatician will have the chance to be incorporated in cutting-edge research conducted in the Vlachos Lab, the Spatial Technologies Unit in Beth Israel Deaconess Medical Center, Harvard Medical School, and the Broad Institute of MIT and Harvard.

The position aims for candidates with a strong quantitative and computational background with extensive experience in genomics/transcriptomics (analysis of different bulk/single cell/spatial Next Generation sequencing Techniques as well as development of novel methods).

Our location within the CRI, the first Institute for RNA Medicine in Boston, Harvard Medical School, and the Broad Institute of MIT and Harvard, creates a unique environment for avant-garde research and scientific growth. The researcher will receive training on research, grant writing, career development, and mentoring. She/he will have the opportunity to lead impactful projects and collaborate directly with an extensive network of leading researchers and companies in the US and internationally. Successful applicants will receive a competitive remuneration and benefits package.

Essential Skills

· Extensive experience in handling and analyzing Next Generation Sequencing data

· PhD in a relevant subject area (Computational Biology, Population Genetics/Genomics, Bioinformatics, Biostatistics)

· Strong quantitative background (e.g. BSc in Computer Science, Applied Math, Engineering, Biostatistics)

· Experience in bioinformatics/data analysis using R/Bioconductor

· Experience in linux-based environments and high-performance computing

· Great programming skills

· Effective science communication

Ideal Skills

· Single cell and/or spatial -omics data analysis experience

· Strong publishing record

· Lead and coordinate extensive projects

For methods builders we also welcome links to github/bitbucket pages, and relevant bioinformatics/computational biology/machine learning community contributions.

We are an equal Opportunity Employer and we welcome applications from women, persons with disabilities, protected veterans, and members of minority groups. International applicants are welcome to apply.'