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Computational Biologist, Immune Cell Repolarization

Biohub· R&D
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Hybrid (New York, NY)$153k - $191kFull-timePosted 1mo ago

About the role

Computational biologist with ML and transcriptomic data analyses to join Biohub NY’s Immune Cell Re-Programming group, collaborating across Columbia, Rockefeller, and Yale, to develop computational methods leveraging multi-omics for immune cell reprogramming and anti-tumor strategies.

Responsibilities

  • Contribute to a dynamic, innovative, and collaborative program that aligns with the mission of Biohub NY.
  • Develop, apply, and evaluate cutting-edge computational / AI methodologies using data generated from across all research groups and incorporating relevant available datasets to develop mechanistic models of tumor-immune-stromal crosstalk.
  • Collaborate within an interdisciplinary research environment to develop, test, and validate models.
  • Engage with colleagues throughout the Biohub to uphold our values of scholarly excellence, innovation, open communication, hands-on hacking, and partnership.
  • Communicate progress and results with colleagues inside and outside of your team.
  • Publish and disseminate impactful findings through preprints (medRxiv, bioRxiv) and/or software repositories (e.g., GitHub).
  • Work with the Biohub team to patent and license technologies resulting from your research.

Qualifications

  • PhD in Systems Biology, AI / Machine learning, Statistics or MS plus relevant job experience.
  • 1-2 years of relevant biomedical science experience, demonstrating a deep understanding of cellular biology, transcription and protein signal transduction.
  • Experience demonstrating the ability to implement, evaluate, and create new computational methodologies that leverage machine learning, statistics, and AI for biological research and discovery.
  • Experience programming in R and Python.
  • Experience in building and evaluating machine learning and/or neural network models on biological data, with a deep understanding of feature selection, regularization, model introspection, and interpretability.
  • Proficiency in using and modifying probabilistic learning or deep learning models such as RNNs, GNNs, protein sequence models, or natural language processing models.
  • Proven track record of individual innovation, as well as a strong ability to work collaboratively.
  • Outstanding interpersonal and communication skills.
  • Demonstrated commitment to open science and alignment with the mission and values of Biohub.

Skills

Required:Machine learning / AI for biological dataTranscriptomic data analysisR and Python programmingML/NLP/Graph-based modelsCommunication / collaboration

Benefits

  • Provides a generous employer match on employee 401(k) contributions to support planning for the future.
  • Paid time off to volunteer at an organization of your choice.
  • Funding for select family-forming benefits.
  • Relocation support for employees who need assistance moving
Last updated Sep 3, 2026. Interested? Apply on the company site.

About Biohub

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