Director, Computational Chemistry

2 weeks ago

San Diego, United States X4 Life Sciences Full time

About the Role:

An innovative biotech company focused on addressing complex challenges in drug discovery is seeking an accomplished Director of Computational Drug Discovery. This leader will drive the development and application of advanced physics-based algorithms and machine learning techniques to overcome critical bottlenecks in drug design. The ideal candidate will bring a proven track record of leading teams in computational science, particularly in developing sophisticated software infrastructure to support drug discovery efforts.


Key Responsibilities:

  • Lead Computational Strategy: Oversee and drive the development of cutting-edge software infrastructure and computational workflows that accelerate drug discovery efforts.
  • Algorithm Development: Implement and scale innovative physics-based methods and machine learning algorithms to optimize the drug discovery pipeline.
  • Collaboration: Work closely with multidisciplinary teams to understand the specific computational challenges in drug design and implement tailored solutions.
  • Software Engineering Best Practices: Ensure that all code developed is scalable, extensible, and portable, and that the software engineering best practices are consistently applied.
  • Innovative Solutions: Stay at the forefront of scientific and computational trends, identifying new approaches that can be integrated into the platform to enhance our drug discovery capabilities.
  • Outsourced Management: Manage outsourced software development projects and ensure quality and performance align with company objectives.
  • HPC and Parallel Programming: Oversee the management of high-performance computing (HPC) clusters, ensuring efficient use of resources and implementation of parallel programming techniques.


Skills and Qualifications:

  • Molecular Modeling Expertise: Extensive experience in molecular modeling and molecular dynamics techniques, with proficiency in tools such as AMBER or OpenMM.
  • Advanced Computational Knowledge: Strong foundation in scientific algorithm development using frameworks such as PyTorch, JAX, etc., with a focus on physics-based methods.
  • Software Development Experience: Proficient in Python and C/C++, with a deep understanding of scientific software engineering best practices.
  • Parallel Programming & HPC: Experience in parallel computing with MPI, OpenMP, OpenACC, CUDA C/C++/Fortran, and managing HPC clusters (both CPU and GPU-based).
  • Workflow Management: Familiarity with workflow frameworks like pySLURM or equivalent HPC job scheduling systems.
  • Containerization: Proficient in using and deploying containers in scientific computing environments.

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