Scientist I, Computational Biology

4 days left

Cambridge, Massachusetts, US
May 01, 2021
May 19, 2021
Employment Type
Full time
Salary Type
Job Description

Biogen has been leading innovative scientific research with the goal to defeat devastating neurological diseases. We rely on the deep scientific expertise and courage of our research and development teams to invent transformative medicines that benefit society.

We are seeking a computational biologist to join the Genome Informatics team within Translational Biology. Our group has multiple functions within the organization, including roles as computational biology primary contacts for exploratory, portfolio and clinical programs in Research, maintenance of enterprise omics data exploration and integration tools, and development of new algorithms and analytical pipelines. Our work supports many facets of drug development - from target validation, lead optimization, biomarker identification and evaluation, and analysis of genomics data from patient cohorts.

The desired candidate will be a computational biologist or bioinformatician who has a thorough understanding of genomics technologies and analytical approaches (secondary and tertiary analysis), with practical experience of their application to the molecular profiling of model in vitro and in vivo systems as well as in human populations. The candidate will be self-driven and have the independence to act as a partner for bench scientists, requiring the development of disease area specific knowledge, expertise to advise on study design, and the ability to interpret analytical results in the context of the program needs.

A track record of working in a cross-functional capacity and leading analytics projects independently is preferred. Experience in Biogen's focus area of neurological, neurodegenerative diseases will be a plus.

· Follow and establish best practices for the analysis and interpretation of NGS data (RNAseq, scRNAseq, miRNAseq, WGS/targeted DNAseq) generated from the NGS lab within Biogen or external sources. Assist in technical troubleshooting, improve and create new workflows as needed.

· Be key partner for disease area scientists to provide analytics support, ingest external datasets, advise on study design, review targets and propose computational and experimental approaches that advance programs.

· Train bench scientists on in-house developed enterprise omics tools that enable generating biological insights from data.

. Apply practical knowledge of latest genomics and analytics technologies - e.g. pathway and network analyses, single cell molecule sequencing, spatial transcriptomics, isoform and splice site identification, machine learning/artificial intelligence for drug discovery

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