
Associate Director, Antibody Engineering
Insilico Search Partners, New York, NY, United States
Associate Director, Computational Scientist – Antibody & Biologics AI Design
Location: New York, NY
Overview
We are seeking an innovative Computational Scientist with deep expertise in antibody and biologics modeling to help transform therapeutic discovery. This role offers the opportunity to apply cutting‑edge AI/ML and generative design approaches to enable de novo antibody design, optimization, and developability assessments across multiple biologic modalities.
Key Responsibilities
- Antibody & Biologics Modeling:
- Build and deploy next-generation modeling workflows for antibodies and complex biologics, including structure prediction, humanization, developability, and bispecific/T-cell engager design.
- Apply advanced AI/ML and generative modeling methods to design novel antibody sequences, enhance affinity and specificity, and accelerate optimization cycles.
- Cross‑Functional Collaboration:
- Work closely with discovery teams, structural biologists, and experimental scientists to integrate computational insights with lab validation.
- Evaluate and implement emerging computational platforms and AI frameworks that improve antibody design, manufacturability, and scalability.
- Scientific Communication:
- Present findings to multidisciplinary teams, contribute to publications and patents, and help shape the biologics discovery strategy.
Qualifications
- Ph.D. in Computational Biology, Biophysics, Bioinformatics , or related field, with 5+ years of post‑PhD industry experience in antibody/biologics drug discovery.
- Demonstrated expertise in antibody modeling , bispecifics , TCEs , or protein engineering .
- Experience applying AI/ML or generative modeling methods to protein or antibody design.
- Proficiency with platforms such as Schrödinger, MOE, Rosetta, or AlphaFold , and coding skills in Python or R .
- Proven ability to communicate across scientific disciplines and deliver impactful results.
Seniority Level
Mid‑Senior level
Employment Type
Full‑time
Job Function
Research
#J-18808-Ljbffr