Senior Scientist, Computational Chemistry/ML Job at EPM Scientific - Phaidon International, Boston, MA

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  • EPM Scientific - Phaidon International
  • Boston, MA

Job Description

Title: Senior Scientist Location: Boston, MA Company Summary: Currently partnered with a leading biotech incubator looking for a highly skilled computational scientist to develop and deploy cutting-edge molecular simulation technologies. This is a hands-on role requiring expertise in algorithm development, molecular dynamics, and machine learning applications. You will pioneer efforts to create scalable, production-level modeling pipelines that redefine how molecular interactions are understood and utilized in drug discovery. Responsibilities: Develop and implement advanced methods for molecular simulation, including AI-enhanced molecular dynamics and machine-learned force fields. Build robust, scalable cloud-based workflows for modeling biomolecular systems such as proteins, peptides, nucleic acids, and small molecules. Drive the integration of novel algorithms into existing computational pipelines to accelerate therapeutic development. Collaborate with interdisciplinary teams to address complex R&D challenges, ensuring computational tools are aligned with project needs. Validate, benchmark, and deploy innovative approaches for enhanced sampling, free energy calculations, and structure prediction. Qualifications: Ph.D. in Computational Chemistry, Biophysics, or related field with a focus on molecular simulation. Proven track record of developing and implementing novel algorithms for biomolecular simulation. Strong programming skills in languages like Python or C++, with experience in molecular simulation tools (e.g., OpenMM, GROMACS, AMBER, CHARMM). Familiarity with protein interactions such as: DiffDock, Autodock, Dock, Rosetta, RoseTTAFold-AllAtom. Experience with machine learning frameworks (PyTorch, JAX) and cloud computing environments (AWS, Docker, Kubernetes). Expertise in AI-derived or polarizable force fields, enhanced sampling techniques, and free energy calculations. Demonstrated ability to scale computational workflows and optimize pipelines for large datasets. #J-18808-Ljbffr EPM Scientific - Phaidon International

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