Recludix Pharma is a venture capital-funded biotechnology company located in San Diego, California and Cambridge, Massachusetts. We are engaged in small molecule drug discovery for the treatment of targeted patient populations in autoimmune disease and oncology. Recludix Pharma is looking for experienced candidates who desire to work in a dynamic early-stage startup environment as a member of our Cambridge/San Diego team.

JOB SUMMARY:

We are seeking a highly skilled computational chemist to advance drug discovery using advanced molecular dynamics (MD) simulation methods. The ideal candidate will have demonstrated experience impacting drug discovery programs, leveraging cutting-edge physics-based modeling and modern generative methods to accelerate molecular discovery. As a key contributor you will collaborate with medicinal chemists, structural biologists and biologists to advance groundbreaking medicines.

QUALIFICATIONS:

• Ph.D or M.S with equivalent experience level in Computational Chemistry, Theoretical Chemistry, Biophysics, Machine Learning, or a related field with a minimum of 3+ years of Pharmaceutical / Biotechnology industry experience
• Expertise in a broad variety of computational techniques is essential, particularly molecular docking, structure-based ligand design and optimization, pharmacophore development.
• Proficiency in state-of-the-art commercial and open-source software tools (e.g., CCG, KNIME, PyMOL)
• Experience working with high-performance computing (HPC) environments and cloud platforms (AWS, etc.).
• Skilled in scientific programming (e.g. Python, Pipeline Pilot), data analytics, database-related skills and familiarity with the Linux command-line environment.
• Excellent communication, interpersonal and organizational skills are essential.

• Key member of a multidisciplinary team of medicinal chemistry, structure biology, discovery technologies, and biology and guide the team by providing computational expertise in structure-based drug design.
• Perform classical molecular modeling tasks such as MM optimization, equilibrium and accelerated MD simulations, in-silico docking, FEP calculations, etc.
• Utilize advanced computational techniques and tools to design and optimize new drug candidates and drive decision-making in drug discovery.
• Provide project teams with computational strategies to inform, influence, and prioritize designs for potency/selectivity, structure-activity relationships, methods to understand on- and off-target activity, physicochemical property-driven lead optimization, and generation of predictive models.
• Integrate DNA-encoded library (DEL) analysis capabilities with computational workflows to expand hit finding capabilities.
• Summarize your work and present actionable conclusions to interdisciplinary teams of structure biology medicinal chemists, and biologists at internal meetings.
• Advancing our modeling capabilities through invention, implementation, and application of new methodologies