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Scientist - Computational Biology

Immunitas Therapeutics
Waltham, Massachusetts, US
Closing date
Jun 28, 2022

View more

Consultancy/Private Sector
Informatics / GIS
Statistics, Biology
Salary Type
Employment Type
Full time
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Immunitas Therapeutics: Scientist - Computational Biology

Position Overview

We are seeking a collaborative and curious individual to join the computational biology team as a Scientist or higher level to help discover new cancer drug targets and bring novel immunotherapies to patients in need.

The candidate will be part of a strong computational biology team responsible for developing and applying cutting-edge computational and statistical techniques to diverse single-cell RNA-seq and spatial transcriptomic datasets. The candidate will work closely with biologists to design computational analyses and experiments for addressing pressing questions to discover new drug targets and advance existing programs to the clinic. In addition, the candidate will help develop the company's in-house computational tools and databases to empower the drug discovery effort.

The candidate should be proficient in UNIX and fluent in either R or Python. The candidate should have experience working with high-dimensional genomics data and have a working knowledge of molecular and cell biology. The candidate should be coachable, determined, responsible, proactive, and able to collaborate with other team members.


  • Work closely with biologists to understand the pressing biological questions and design computational approaches for addressing them
  • Run and refine downstream analysis for in-house and public single-cell RNA-seq datasets which includes normalization, dimension reduction, cell annotation, differential expression, gene module discovery, ligand-receptor interaction analysis, etc.
  • Run established single-cell RNA-seq pre-processing pipelines within the Google Cloud platform
  • Read the scientific literature to find new angles and methods to address the biological questions at hand
  • Troubleshoot and employ statistical machine learning methods to analyze single-cell data
  • Communicate results clearly to both internal and external stakeholders

  • Ph.D. in computational biology, bioinformatics, biostatistics, computer science, cell biology, immunology, or related fields.
  • Good knowledge of immunology is a plus but not required.
  • Proficient with the UNIX command-line.
  • Cloud computing experience is a plus, but not required. Experience working with high-performance computing clusters (HPC) will be helpful.

· Basic git and github literacy preferred
  • Fluent in either Python or R programming languages.
  • Good understanding of routine single-cell RNA-seq analysis workflow. Hands-on experience in analyzing single-cell data and knowing packages such as Seurat/Scanpy and other Bioconductor packages are preferred.
  • Strong organizational skills and ability to prioritize and multitask efficiently in a results-oriented, dynamic environment.
  • Strong interpersonal skills and ability to work in teams, and communication skills to present the data.

To Apply

Please send resume and brief introduction paragraph to

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