Research Scientist – Molecular Dynamics

Role Overview

• Develop and execute innovative computational strategies, leveraging molecular dynamics, enhanced sampling, and free energy methods to solve complex challenges in drug discovery
• Partner closely with cross-functional teams including medicinal chemists, structural biologists, and AI/ML researchers to integrate computational insights and advance our drug discovery projects
• Analyze, interpret, and effectively present complex simulation data to both technical and non-technical audiences
• Contribute to GPCR Structure-Based Drug Discovery projects by applying computational chemistry and CADD approaches
• Stay up-to-date with the latest advancements in molecular modeling, enhanced sampling methods, and binding free energy approaches, integrating new methodologies to continuously improve our workflows

Requirements

• PhD in biophysical chemistry, computational chemistry or related field
• A minimum of 4 years of hands-on experience in a research lab, pharmaceutical company, or biotech startup, with a focus on molecular dynamics and free energy calculations
• Deep understanding of thermodynamics, binding free energy, and enhanced sampling methods
• Proficiency in molecular dynamics simulation packages (e.g., Tinker, GROMACS, AMBER, OpenMM)
• Extensive experience with Free Energy (FE) methods, including Absolute, Relative, and Hydration FE calculations, and various enhanced sampling approaches
• Proven experience applying FE methods to a wide range of macromolecule-ligand systems
• Hands-on experience with High-Performance Computing (HPC) environments, including the use of job schedulers like Slurm
• Experience in developing, implementing, or optimizing new FE or enhanced sampling methods
• Experience with classical (AMBER, CHARMM, OPLS) and polarizable force fields (AMOEBA)
• Familiarity with advanced simulation package options, such as performance optimization and force field tuning
• Familiarity with ML-based potentials for molecular dynamics simulations, including an understanding of their development and application
• Skilled in using various computational tools to analyze and visualize interactions from MD simulations and docking poses
• Proven experience and deep understanding of GPCR structure, function, and signaling pathways.

Benefits

• Health insurance and provident fund 100% covered
• Lunch vouchers worth €9 covered at 50%.