ML & Molecular simulation Scientist

What if your expertise in machine learning and molecular modelling could accelerate the development of tomorrow’s life-changing medicines?

R&D Partners is seeking an ML & Molecular Simulation Scientist to develop and apply cutting-edge methods at the intersection of 3D molecular simulation and machine learning. This role offers the opportunity to contribute directly to drug discovery programs by integrating physics-based simulations with modern AI techniques.

Applicants must have legal authorization to work in the United States.

Responsibilities:

• Build and apply ML models informed by 3D structural data, including geometric deep learning, equivariant neural networks, and diffusion-based generative models for molecular design and property prediction.
• Integrate physics-based and ML-driven approaches, combining force field methods, quantum chemistry, and structure-based design to enhance accuracy and throughput.
• Develop and apply simulation methods such as molecular dynamics (MD), enhanced sampling, metadynamics, replica exchange, umbrella sampling, and free energy calculations (FEP-TI) to support active drug discovery programs.
• Contribute to platform development by improving generative AI and scoring capabilities, focusing on 3D methods and next-gen force fields.
• Collaborate with CADD and discovery scientists to apply computational methods across the drug discovery pipeline, from target structure analysis to lead optimization.
• Stay current with advancements in geometric ML, biomolecular simulation, and computational drug design, implementing and adapting methods from the latest literature.
• Communicate scientific results clearly to multidisciplinary teams, including experimental chemists and biologists.

Key Skills and Requirements:

• Education: PhD preferred in computer science, machine learning, chemical engineering, biophysics, physics, or a closely related field. Postdoctoral or industry experience is a plus.
• Machine Learning Expertise: Practical experience with 3D machine learning, geometric deep learning, graph neural networks, equivariant architectures (e.g., SE3/E3 networks), or diffusion models applied to molecular data.
• Molecular Simulation Expertise: Deep hands-on experience with MD, enhanced sampling, and/or free energy methods using tools like GROMACS, AMBER, OpenMM, or NAMD.
• Drug Design Knowledge: Familiarity with structure-based drug design workflows, docking, binding site analysis, and protein-ligand interaction modeling using tools like MOE or PyMOL.
• Technical Proficiency: Strong skills in Python and scientific computing libraries (e.g., PyTorch, JAX, NumPy, MDAnalysis, RDKit) and comfort with HPC environments and scripting for large-scale simulation workflows.
• Track Record: Demonstrated success in applying computational methods to real scientific problems through publications, open-source contributions, or industry impact.
• Soft Skills: Collaborative, curious, and able to balance rigorous method development with fast-paced discovery work.

Nice to Have:

• Familiarity with cheminformatics and ADMET property prediction.
• Contributions to open-source simulation or ML tooling.

Compensation:

• $190 000 – $200 000.00 Per Annum

For more information, please contact Indre Semeskeviciute.

If you are interested in applying to this exciting opportunity, then please click ‘Apply’ or to speak to one of our specialists visit the ‘Contact Us’ page.

R&D Partners is a leading life sciences recruiter focused on finding exceptional people and matching them with the finest positions across the globe. R&D Partners is acting as an Employment Agency in relation to this vacancy.

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