Consultant Scientist, Computer Aided Drug Design (CADD)

Key Responsibilities

• Design small molecule (and related modality) therapeutics using structural/simulation/ML/assay data, ensuring alignment with the requirements and timelines of our drug discovery projects, and leading computational analysis and design activities on cross-functional projects.
• Integrate knowledge of relevant computational tools and approaches, as well as key aspects of medicinal chemistry and compound property optimization, for all project stages from target selection and druggability analysis to clinical candidate nomination.
• Collaborate with the computational development team to align priorities between platform application development and R&D projects.
• Develop modifications and drive improvements in internal applications, building on our internal physics-based simulation capabilities and assessment of fidelity and accuracy of calculations.
• Train and mentor team members across the organization to build understanding of modeling and AI/ML concepts and how they address project team needs.

Requirements

• PhD in computational chemistry, organic or physical chemistry, physics, or a closely related field
• Minimum of 5 years computer-aided drug design (CADD) or related biotech/pharma experience, with expertise accelerating small molecule drug discovery projects from target tractability and hit identification, through lead optimization (demonstrated by peer reviewed publications and inventorship status on patent applications)
• Demonstrated experience and understanding of physics-based, AI/ML, and generative computational approaches to drug discovery
• Excellent communication and collaboration skills, with the ability to work well in a multidisciplinary environment
• Excellent organizational skills and attention to detail, with a strong passion for learning new concepts and technologies

Additional Qualifications

• Proficiency in scientific programming (e.g. Python, R, C++)
• Proficiency in molecular simulation packages (e.g. AMBER, OpenMM, NAMD, Gromacs)
• Proficiency in data science and machine learning tools (e.g. scikit-learn, pytorch)
• Experience mentoring interns, co-ops, and junior scientists