Featured Opportunities in Life Sciences & Healthcare

This role focuses on advancing antibody and biologics discovery through computational modeling and AI-driven approaches. The position involves developing and applying modeling workflows for antibodies and biologics, including protein structure prediction, antibody humanization, developability assessments, and protein–protein interaction modeling. A key part of the role is using AI/ML and generative modeling techniques to support de novo antibody design, affinity maturation, and optimization across multiple therapeutic modalities such as monoclonal antibodies, bispecifics, and T-cell engagers. The role also contributes to tool development and evaluation, identifying and implementing next-generation computational approaches that improve design, manufacturability, and overall drug discovery outcomes.

This position works closely with cross-functional teams, including discovery scientists, structural biologists, and immunologists, to integrate computational insights with experimental validation. Responsibilities include communicating results to multidisciplinary teams and contributing to publications, patents, and scientific presentations, while helping shape biologics discovery strategy. Candidates should have a PhD in computational biology, bioinformatics, biophysics, or a related field, along with experience in antibody or protein modeling and hands-on experience applying AI/ML methods to biologics. Proficiency with computational platforms (e.g., Schrödinger, Rosetta, AlphaFold) and programming in Python or R is expected, along with strong collaboration and communication skills.

The anticipated base salary range for this position is $200,000 - $250,000 annually and will require relocation to New York City. This range reflects a good faith estimate of compensation based on experience and qualifications. Final compensation will be determined based on a variety of factors, including experience, qualifications, level, and overall scope of the role.