Join Us

On-Site or Remote

Full-Time, Contract/Direct Hire

Lead Research Scientist / Director of Computational Biology

We are seeking a highly skilled AI Scientist to work as Senior Computational Antibody Engineer to spearhead our in silico affinity maturation efforts as part of a cutting-edge antibody design pipeline. This role is responsible for developing, maintaining, and optimizing our deep learning workflows using the latest state-of-the-art models (e.g., ESM3, RFdiffusion v2.0, ProteinMPNN v2.0, and AlphaFold3) to predict beneficial mutations and generate optimized antibody variants.

• Data Retrieval & Curation:
  • Retrieve and curate antibody sequences and 3D structures from databases such as SAbDab, PDB, ABSD, and OAS.
  • Ensure data quality via sequence annotation tools (e.g., ANARCI) and integrate biophysical data (e.g., DOTAD metrics).
• Deep Learning Pipeline Development:
  • Implement and optimize advanced protein language models (ESM3) for mutation scanning and affinity prediction.
  • Develop custom Python scripts for automated mutation scanning, scoring, and ranking.
• Generative Modeling Integration:
  • Fine-tune and integrate diffusion-based generative models (RFdiffusion v2.0) to generate 3D backbone structures.
  • Collaborate with the team to optimize downstream sequence design using ProteinMPNN v2.0.
• Validation & Iteration:
  • Oversee in silico validation using docking (RoseTTAFold3/RosettaDock) and MD simulations (GROMACS 2023) to assess structural fidelity and binding affinity.
  • Develop composite scoring functions that integrate deep learning outputs, structural metrics, and docking energies.
• Pipeline Automation:
  • Contribute to the integration of all computational modules into an automated pipeline using Snakemake/Nextflow.
  • Ensure reproducibility by maintaining detailed documentation, version control, and containerized environments (Docker/Singularity).
• Collaboration & Communication:
  • Work closely with computational biologists and other team members in daily stand-ups and review meetings.
  • Document experimental results, maintain internal logs, and contribute to project reports.

• Ph.D. or Master’s degree in Computational Biology, Bioinformatics, Computer Science, or a related field.
• 3+ years of experience in computational antibody design or related protein engineering fields.
• Demonstrated expertise in deep learning frameworks (PyTorch/TensorFlow) and experience with transformer-based models (e.g., ESM3).
• Proven programming skills in Python, with experience in developing automated pipelines and custom scripts.
• Familiarity with structural bioinformatics tools (e.g., AlphaFold, Rosetta) and MD simulation packages (e.g., GROMACS).
• Experience with high-performance computing environments and containerization (Docker/Singularity) is a plus.

• Strong analytical and problem-solving skills.
• Ability to work independently and as part of a multidisciplinary team.
• Excellent written and verbal communication skills.