Research Scientist, AI​/ML; BHN - NY

Biohub is leading the new era of AI-powered biology to cure or prevent disease through its 501c3 medical research organization, with the support of the Chan Zuckerberg Initiative.

The Chan Zuckerberg Biohub Network (https://(Use the "Apply for this Job" box below).) is a group of nonprofit research institutes that bring together scientists, engineers, and physicians with the goal of pursuing grand scientific challenges on 10- to 15-year time horizons. The CZ Biohub Network focuses on understanding underlying mechanisms of disease and developing new technologies that will lead to actionable diagnostics and effective therapies.

• We pursue large scientific challenges that cannot be pursued in conventional environments
• We enable individual investigators to pursue their riskiest and most innovative ideas
• The technologies developed at the CZ Biohub Network facilitate research by scientists and clinicians at our home institutions and beyond

Diversity of thought, ideas, and perspectives are at the heart of CZ Biohub Network and enable disruptive innovation and scholarly excellence. We are committed to cultivating an organization where all colleagues feel inspired and know their work makes an important contribution.

The Biohub Network is seeking an accomplished computational biologist and machine learning/AI specialist to join our interdisciplinary team. This role requires experience in research settings, a background in biology, and a proven ability to design, evaluate, and publish innovative computational methodologies that leverage machine learning, statistics, language modelling, and AI to advance biological research and discovery. Research projects to accelerate the rate of scientific discovery will be assigned by the President of the New York location, and in collaboration with research teams across the organization.

The ideal candidate will have a strong track record of accomplishments and a dedication to collaborative work within a highly interdisciplinary environment.

This role is based out of the New York location.

This role is a hybrid role and will require you to be onsite approximately 3 days a week at our Headquarters. Will you be able to commit to this?

• Contribute to a dynamic, innovative, and collaborative program that aligns with the mission of CZ Biohub NY.
• Develop and evaluate cutting‑edge computational / AI methodologies using data generated from across all research groups and incorporating relevant available datasets for to develop predictive models.
• 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., Git Hub).
• Work with the CZ Biohub team to patent and license technologies resulting from your research.

• PhD in Computational Biology, AI / Machine learning, Applied Statistics or a MS plus relevant job experience.
• Background in relevant areas of biomedical science, demonstrating a deep understanding of cellular biology, transcription and protein signal transduction.
• 2-4 years of post‑doctoral and/or industry 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 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…