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Director of Computational Biology and AI/ML Platform Job Opening In Boston – Now Hiring Commonwealth Sciences, Inc.


Job description

Position located in Boston, MA


Responsibilities of the Director of Computational Biology and AI/ML Platform:

  • Will lead the development and implementation of our computational infrastructure for antibody discovery and optimization.

  • Design and implement the computational platform architecture for antibody discovery, integrating ML/DL models, structural biology tools, and high-throughput screening data analysis into the pipeline

  • Develop and deploy ML models for antibody-antigen binding prediction, affinity maturation, and developability assessment

  • Develop state-of-the-art deep learning models for structure-based antibody design, antibody sequence design, antibody-antigen co-folding, and antibody-antigen binding prediction

  • Lead the integration of AlphaFold, Rosetta Antibody/Rosetta Fold, Boltz-1, and other state-of-the-art protein structure prediction tools into the discovery pipeline

  • Create and maintain computational workflows for analyzing large-scale screening data (phage display, yeast display, NGS data) to identify lead candidates

  • Partner with teammates in Platform Engineering and Discovery to identify key challenges and design innovative, AI-driven solutions using in silico and in vitro validation results

  • Implement structural modeling pipelines including homology modeling, molecular dynamics simulations, and protein-protein docking for antibody optimization

  • Use expertise to influence the Founding and research team’s agenda while maintaining a high level of responsibility and accountability for work deliverables
  • Requirements of the Director of Computational Biology and AI/ML Platform:

  • PhD in Computational Biology, Bioinformatics, Computer Science, Physics, or related quantitative field with 5+ years of industry experience in biologics/antibody discovery

  • Proven expertise in machine learning and deep learning frameworks (PyTorch, TensorFlow, JAX) and state-of the-art AI algorithms applied to protein design and structure prediction

  • Strong background in protein, molecular dynamics, and antibody-specific computational tools and databases (IMGT, AbNum, Chothia numbering, etc.)

  • Skilled in high-throughput data analysis (NGS, display technologies) and structural biologysoftware (PyMOL, Rosetta, Schrödinger suite, MOE)

  • Proficiency in Python, with experience in R, C++, or Julia as a plus

  • Knowledge of antibody biology and therapeutic antibody development process is a plus.
  • Required Skill Profession

    Mathematical Science Occupations


    • Job Details

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