Computational Protein Scientist

Compensation

$160,000 - $200,000 + Equity + Benefits

A venture-backed biotech company developing next-generation protein therapeutics is looking to add a Computational Protein Scientist to its growing team. This individual will sit at the intersection of protein design, structural biology, machine learning, and biophysics, helping drive the design of novel proteins whose function depends on precise control of conformational behavior.

As one of the first computational hires focused on protein design, you'll have the opportunity to shape scientific strategy, work closely with experimental teams, and apply state-of-the-art AI models to real-world therapeutic challenges.

• Apply modern protein structure prediction and design models (e.g. Alpha Fold, RoseTTAFold, RF diffusion, ProteinMPNN, ESM-based models) to design and prioritize novel protein variants.
• Combine machine learning approaches with physics-based reasoning around stability, binding, energetics, and conformational dynamics.
• Generate computational hypotheses and partner closely with biology and protein engineering teams to validate designs experimentally.
• Build and maintain scalable workflows for protein design, structural analysis, and candidate prioritization.
• Help establish best practices for integrating AI-driven protein design into discovery programs.

• PhD in Computational Biology, Biophysics, Computational Chemistry, Structural Biology, Machine Learning for Molecular Sciences, or a related discipline.
• Deep experience working with protein structure prediction models and an understanding of their strengths, limitations, and confidence metrics.
• Hands‑on experience with protein design methodologies, generative protein models, inverse folding approaches, and structure‑based design workflows.
• Strong programming skills in Python and familiarity with scientific computing tools such as PyTorch, Num Py, Sci Py, Biopython, or related libraries.
• Strong intuition for sequence‑structure‑function relationships, protein energetics, and conformational behavior.
• Demonstrated ability to translate computational predictions into experimentally testable outcomes.

• Experience with molecular dynamics simulations, enhanced sampling methods, or free energy calculations.
• Background in protein engineering, enzyme engineering, or therapeutic protein design.
• Familiarity with cryo‑EM, structural biology datasets, or integrating experimental data into computational workflows.
• Experience running large‑scale GPU workloads in cloud environments such as AWS or GCP.
• Publications or industry experience involving protein design, molecular modeling, or AI for biology.
• Comfortable operating in a fast‑paced startup environment and building new computational capabilities from the ground up.

• Opportunity to be an early scientific hire at a company applying cutting‑edge AI and protein engineering to therapeutic development.
• Highly collaborative environment with direct influence on scientific direction and platform development.
• Competitive compensation, equity, and benefits package.
• Chance to work on challenging protein design problems with meaningful real‑world impact.