Senior Scientists, Computational Biology

Data Sciences

Job Description

We are seeking innovative and collaborative computational biologists, data scientists and AI researchers at all levels to work on groundbreaking single cell genomics projects changing the landscape of therapies for cancer and autoimmune diseases. Team members will play key roles in integrating and mining multiple internal and external datasets at massive scale generated by single cell RNA-seq data from human patients. A critical component of the job will be to develop and implement innovative analysis strategies to generate focused hypotheses for the identification of new therapeutic targets.


Successful candidates will play a key role in a dynamic and growing team of biological and computational scientists using cutting edge genomics techniques, single cell sequencing and machine learning for the discovery of new targets. Primary responsibilities will be to:


  • Desire to work in a fast-paced startup environment to integrate the latest in computational biology, single cell genomics and cutting-edge machine learning and AI systems.
  • Ability to thrive in a dynamic, rapidly growing startup advancing precision medicine and drug discovery while partnering with top tier venture funds such as Third Rock Ventures, Google Ventures and others.
  • Engage with Celsius ThinkLab advisors at the forefront of single cell genomics including Nir Yosef, Barbara Engelhardt, and Peter Kharchenko.


  • Generate meaningful biomedical and clinical hypotheses from single cell genomics data in immuno-oncology and autoimmune diseases.
  • Prioritize and validate drug discovery targets through the latest in machine learning and data science.
  • Apply or develop new computational biology algorithms and data-mining techniques for integrative analysis and visualization of big data in the biology domain.
  • Develop a whole biology AI stack for genomics-based drug target discovery.
  • Work with biologists to implement new experiments and validate them using AI-assisted approaches in an active learning paradigm.


  • A Ph.D. in Bioinformatics, Computer Science, Biology, Genetics or equivalent, and a minimum of 5 years of experience in computational biology and genomics required.
  • A strong background in cancer biology and/or single cell genomics and/or immunology.
  • Strong scientific background and publication record with proven high levels of performance.
  • Ability to innovate, apply and develop new tools for the integrative analysis and visualization of multi-dimensional genomics datasets.
  • Experience with machine learning algorithms and data mining methods.
  • Proficiency with Python, R or other scripting language for statistical computing and graphics.
  • Experience with cloud computing is a plus.
  • Ability to adapt to increasing scope and complexity of work brought on by growth/change and helps others manage through change.
  • Strong written, oral and public speaking communication skills.
  • Knowledge of industry trends and ability to utilize that knowledge to determine the most efficient ways to meet business needs.