ML & Molecular Simulation Scientist

Role: ML & Molecular Simulation Scientist specializing in integrating 3D molecular simulation with machine learning to advance drug discovery. Responsibilities: develop ML models based on geometric deep learning and equivariant neural networks, apply physics-based and data-driven simulation methods (MD, enhanced sampling, free energy calculations), and contribute to the GEMS platform for molecular design. Collaborate with CADD and discovery teams to translate computational insights into lead optimization. Requirements: PhD in computer science, physics, or related field; practical experience with 3D ML models and molecular simulation tools (GROMACS, AMBER, OpenMM); proficiency in Python (PyTorch, JAX, NumPy, RDKit); publication or impact record in computational drug design. HighValue: expertise in geometric ML, molecular dynamics, free energy calculations, structure-based drug design, and large-scale HPC workflows. Nice to Have: knowledge of cheminformatics, ADMET prediction, open-source contributions. WorkSetup: collaborative role focused on cross-disciplinary research, with no explicit location or travel details specified.