Computational Chemist Job at Topos Bio, San Francisco, CA

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  • Topos Bio
  • San Francisco, CA

Job Description

Topos Bio

At Topos Bio, we're pioneering drug discovery for intrinsically disordered proteins-targets that have eluded conventional approaches in neurodegeneration, oncology, and cardiometabolic disease.

We're seeking a Computational Chemist to help generate novel molecules for a variety of targets and collaborate closely with AI researchers and experimental scientists.

What you will do

  • Develop scalable workflows to generate and screen thousands of potential drug candidates
  • Design and run molecular dynamics simulations, applying enhanced sampling methods to characterize protein-ligand binding and conformational dynamics
  • Engineer and optimize data pipelines that handle large-scale molecular simulations and structure-based predictions
  • Build and optimize cheminformatics pipelines for compound filtering, property prediction, fingerprint-based similarity search, and chemical space analysis
  • Collaborate with AI researchers to incorporate simulation data into model training and inference pipelines
  • Bridge scientific rigor with practical results, ensuring computational protocols are both accurate and efficient
  • Communicate technical nuances to cross-functional teams, fostering a shared understanding of capabilities and limitations
  • Stay up to date with the latest research and breakthroughs in computational chemistry, generative models, and molecular simulation
  • Lead external scientific presentations to pharmaceutical partners; Communicate the team's computational approaches for both technical audiences and business partners

What we are looking for

  • PhD in Computational Biophysics, Computational Chemistry, or a related field
  • Experience with molecular modeling, simulation, and generative drug design
  • Proficiency with common computational biophysics software (e.g. AMBER, GROMACS, OpenMM, PLUMED, Schrödinger, OpenEye)
  • Strong background in cheminformatics: molecular fingerprints, QSAR/QSPR, property prediction, scaffold analysis, cheminformatics libraries (e.g., RDKit, OpenBabel)
  • Expert coding in at least one language (Python preferred)
  • Familiarity with HPC cluster or cloud computing environments, containerization, and workflow orchestration
  • Strong communication skills, with the ability to present complex ideas in clear terms

Preferred

  • Experience integrating machine learning techniques for molecular generation
  • Background in quantum chemistry methods (DFT, ab initio) and its application to biomolecular systems
  • Exposure to early-stage drug discovery programs, from target identification to lead optimization

Job Tags

Full time

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