Demo

Computational Scientist

Northreach
Hayward, CA Full Time
POSTED ON 2/27/2025
AVAILABLE BEFORE 5/23/2025

About the Role

An innovative technology company at the forefront of AI-driven protein engineering is looking for a Computational Scientist with expertise in Machine Learning (ML) and Molecular Dynamics (MD). This role will focus on developing advanced computational models to improve protein behaviour prediction, molecular interactions, and stability assessments.

This is an opportunity to work in an interdisciplinary setting, integrating ML techniques with molecular simulations to drive the next generation of protein design and drug discovery tools.

Responsibilities

  • Build and optimize ML-powered molecular dynamics models for predicting protein behaviour.
  • Collaborate with engineers and scientists to integrate computational simulations into broader research workflows.
  • Develop enhanced sampling methods and free energy calculations to refine molecular modelling approaches.
  • Create predictive models for protein-protein and protein-ligand interactions.
  • Stay ahead of cutting-edge advancements in computational biology, molecular simulations, and AI-driven modelling.
  • Present research insights and technical findings to cross-functional teams.

Requirements

  • Ph.D. or equivalent experience in Computational Biology, Structural Biology, Biophysics, or a related field.
  • Deep expertise in Molecular Dynamics simulations, including coarse-grained methods (CGMD).
  • Hands-on experience applying ML techniques to molecular modelling and protein engineering.
  • Strong coding skills in Python, with proficiency in frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Familiarity with free energy calculations, enhanced sampling methods, and AI-driven structure prediction tools.
  • Ability to work in a dynamic, fast-paced research setting with cross-disciplinary teams.
  • Preferred Experience

  • Industry background in computational drug discovery, AI-driven biologics, or protein engineering.
  • Expertise in docking simulations, molecular docking tools (e.g., AutoDock, Rosetta), or quantum mechanics / molecular mechanics (QM / MM) methods.
  • Experience implementing ML models in scientific workflows for biologics research.
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