About the job
Join the Innovative Team at Topos Bio
At Topos Bio, we are at the forefront of drug discovery, focusing on the challenging area of intrinsically disordered proteins—molecular targets that traditional methods have struggled to address, particularly in neurodegeneration, oncology, and cardiometabolic diseases.
We are looking for a passionate and skilled Computational Chemist to join our dynamic team. This role involves the generation of novel molecules across diverse targets and requires close collaboration with AI researchers and experimental scientists to push the boundaries of drug discovery.
Your Responsibilities
Create and optimize scalable workflows for the generation and screening of thousands of potential drug candidates.
Design and execute molecular dynamics simulations, employing advanced sampling methods to analyze protein-ligand interactions and conformational changes.
Develop and refine data pipelines for managing large-scale molecular simulations and structure-based predictions.
Construct and enhance cheminformatics pipelines for compound filtering, property prediction, similarity searching, and chemical space exploration.
Collaborate with AI specialists to integrate simulation data into model training and inference frameworks.
Ensure computational protocols are scientifically sound while delivering practical outcomes.
Effectively communicate complex technical concepts to cross-functional teams, aiding in the understanding of capabilities and limitations.
Remain informed on the latest advancements in computational chemistry, generative models, and molecular simulations.
Lead scientific presentations to pharmaceutical partners, articulating the computational strategies employed by our team to both technical and non-technical audiences.
Qualifications
PhD in Computational Biophysics, Computational Chemistry, or a related discipline.
Demonstrable experience in molecular modeling, simulation, and generative drug design.
Proficient in computational biophysics software (e.g., AMBER, GROMACS, OpenMM, PLUMED, Schrödinger, OpenEye).
Strong foundation in cheminformatics: molecular fingerprints, QSAR/QSPR, property prediction, scaffold analysis, and cheminformatics libraries (e.g., RDKit, OpenBabel).
Expertise in at least one programming language, preferably Python.
Experience with HPC clusters or cloud computing environments, containerization, and workflow management.

