We are seeking a Bioinformatics Research Associate for a role on our computational biology team. This position will help mine single-cell transcriptomics datasets for novel drug targets and help compile our single-cell transcriptomics and neuroanatomical tracing datasets into an integrated resource that we plan to disseminate to the academic community. The successful candidate will incorporate new transcriptomics data into our computational drug discovery platform, both from in-house experiments and public datasets, and will integrate these with databases encoding gene and protein annotations, disease genetics, biological networks, and drug data. The role will require close interaction with experimental scientists to apply methods for data visualization, statistical analysis, clustering, and differential gene expression. Candidates for this role should have experience in the analysis of microarray, bulk RNA sequencing, and single-cell RNA sequencing data, and should be familiar with relational databases and cluster computing. Successful candidates must be enthusiastic to work in a highly collaborative setting, both with computational and experimental scientists.   

 Key Responsibilities:

  • Working interactively with our experimental scientists to assess the gene expression, biochemical function, and disease relevance of prospective drug targets
  • Running our computational engine to add new transcriptomics and neuroscience datasets into the platform, and transforming public datasets for compatibility with our pipeline
  • Testing the performance of software tools and the reproducibility of data analyses; benchmarking competing tools for comparison
  • Implementing diagnostics to troubleshoot the development of novel experimental technologies
  • Contributing to UI and web development to expose our computational tools to users within the firm and external collaborators/partners
  • Staying abreast of the latest developments in relevant bioinformatics methods, particularly in the domains of RNA sequencing, knowledge representation, and drug discovery
  • Participating in code reviews; software deployment and maintenance; iteration planning and timeline estimation; and software design discussions

Qualifications and Education Requirements:

You must have:

  • B.A. or M.S. in Computational Biology, Bioinformatics, Statistics, or a related discipline
  • 1-2 years of experience programming and analyzing NGS datasets
  • Proficiency in R, Python, SQL, Unix/Linux, and Git version control
  • Experience extracting data from biological databases
  • Commitment to rigor, in both quantitative analysis and software development
  • Excellent communication and interpersonal skills (the role requires very close collaboration with both experimental and computational scientists)

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