Associate Director Computational Protein Design

Associate Director Computational Protein Design
Boston, MA
$84-100/hr
6-Month Contract to Hire

The Associate Director Computational Protein Design will lead a group of computational protein engineers supporting in silico design campaigns across the company’s program portfolio. They will set the technical roadmap for computational protein design — the strategy, tools, and workflows by which proteins are discovered, improved, and optimized against portfolio demand.

Associate Director Computational Protein Design Responsibilities:

• Oversee in silico library design across company programs, including campaign scope, selection of design approaches, and interpretation of screening results.
• Guide enzyme discovery and improvement campaigns, using metagenomic sourcing, database mining, and rational protein engineering to discover enzymes with defined function, and to improve catalytic parameters — kcat, Km, Ki, substrate and product selectivity — and biophysical properties including thermostability, colloidal stability, solvent tolerance, and expression, including data-driven model development for iterative improvement and multi-objective optimization.
• Direct de novo design of minibinders against protein and small-molecule targets: scaffold generation, interface design, and computational triage prior to build.
• Drive continuous adoption and advancement of state-of-the-art methods in protein design, and establish best practices for method selection.
• Training and team development — Mentor scientists to deepen their technical capabilities and scientific judgment, and cultivate a collaborative, intellectually open team environment.
• Serve as the organization’s senior technical authority on protein design, advising program leads, business development, and R&D leadership on feasibility, design strategy, and goal setting for a given target.
• Optimize design–build–test–learn loops by interfacing with autonomous robotics, high-throughput screening, and analytics teams to increase assay capacity and data quality while reducing turnaround time.
• Work with automation and data teams to ensure program data is captured, structured, and reusable for model training and data-driven protein engineering.
• Translate design successes into reusable platform capabilities — standardized workflows, internal tooling, benchmarked datasets, and design principles that carry forward to new programs.
• Represent protein design externally with partners and prospective customers; scope technical proposals and define success criteria.

Associate Director Computational Protein Design Requirements:

• PhD in protein engineering, computational biology, biochemistry, biophysics, structural biology, or a related field, with 8+ years of relevant post-degree experience (or MS with 12+); at least some of it in an industrial, program-driven setting.
• Extensive hands-on experience in computational protein design spanning discovery, improvement, and optimization, with demonstrated depth in enzymes.
• Deep command of sequence-based protein design: constructing and curating multiple sequence alignments, and using them to build statistical models (hidden Markov models, substitution matrices, Potts models, variational autoencoders) alongside protein language models such as ESM and BERT-class architectures, applied to variant effect prediction and library design.
• Fluency with AI/ML structural modeling in protein design, including structure and complex prediction (AlphaFold2/3, Boltz, Chai, Protenix), generative design (RFdiffusion and related methods), and inverse folding (ProteinMPNN), with the judgment to know which method suits which problem.
• Fluency with physics-based structural modeling, including Rosetta/PyRosetta design and scoring, residue scanning mutagenesis, molecular dynamics simulations, ??G prediction, molecular docking, and free-energy methods, applied to questions of mechanism, activity, stability, and binding.
• Experience coupling computational design to wet-lab experiments for data-driven protein engineering: assembling campaign datasets and training supervised regression models (regularized linear models, Gaussian processes, gradient-boosted trees) on enzyme activity labels to predict fitness and protein properties.
• Strong scientific programming skills in Python; comfortable working in a cloud/HPC environment with version control, reproducible pipelines, and standard software engineering practice.
• Experience leading people or projects: mentoring scientists, managing at least one direct report, or leading a technical workstream with accountability for delivery.
• Excellent written and verbal communication; able to translate technical tradeoffs into clear recommendations for scientific, commercial, and executive audiences.

Associate Director Computational Protein Design Preferred Qualifications:

• Experience managing a computational protein design or protein engineering team.
• De novo binder design, including miniproteins and engineered scaffolds, against protein and small-molecule targets.
• VHH and antibody optimization: humanization, affinity maturation, targeted epitope design, and developability profiling.
• Industrial biocatalysis: tailoring enzyme performance to demanding reaction environments (pH, temperature, solvent, high substrate load) and aligning design goals with process constraints.
• Computational metagenomics pipelines, large-scale sequence repositories, and clustering tools for mining novel biological functions at scale.
• Delivery against milestones for external partner programs in a platform or client-facing organization.
• Scientific contributions including peer-reviewed literature, patent filings, platform deployments, and technical presentations.