Computational Scientist - Small Molecule Drug Discovery

We are seeking an exceptionally motivated and skilled Computational Scientist to be a core member of our drug discovery team. You will be the primary driver of our computational strategy, applying state-of-the-art CADD and AI/ML techniques to identify, design, and optimize small molecule hits that selectively modulate the TRPV2 channel. This is a chance to have an immediate and direct impact on a challenging target for a potentially life-saving indication.

Responsibilities

• Structure-Based Drug Design (SBDD): Utilize the latest structural data (e.g., Cryo-EM/X-ray) of TRPV2 to perform molecular docking, virtual screening, and protein-ligand dynamics simulations (MD) to identify novel chemotypes.
• Small Molecule Lead Optimization: Collaborate closely with medicinal chemists to design, prioritize, and analyze SAR (Structure-Activity Relationship) data, applying CADD principles to optimize potency, selectivity, and ADMET properties (absorption, distribution, metabolism, excretion, and toxicity).
• Virtual Screening (AI/ML): Develop and implement advanced AI/ML models (e.g., QSAR, deep learning, or generative models) to prioritize compound libraries and predict novel scaffolds with desired properties.
• Mechanism Elucidation: Apply computational biophysics (e.g., QM/MM) to deeply understand the allosteric communication, binding kinetics, and mechanism of action of small molecule modulators on the TRPV2 channel.
• Cross-Functional Collaboration: Act as the computational expert in multidisciplinary project teams, clearly communicating complex data and hypotheses to non-computational biologists and chemists.

Qualifications

• Education: Ph.D. in Computational Chemistry, Computational Biology, Biophysics, Cheminformatics, or a closely related field.
• Experience: [2-5] years of industry (biotech/pharma) or significant post-doctoral experience accelerating small molecule drug discovery projects from hit identification through lead optimization.
• CADD Expertise: Deep, hands-on proficiency with commercial and/or open-source molecular modeling packages (e.g., Schrödinger, OpenEye, GROMACS, AMBER, OpenMM).
• Programming Skills: Expertise in scientific programming, particularly Python (RDKit, Pandas, etc.) for data analysis, pipeline development, and workflow automation.
• Target Experience (Highly Desirable): Prior experience with ion channels (TRPV family) or other membrane proteins is a significant plus.

Why Join Us?

• High Impact: Work on a first-in-class program addressing the devastating consequences of AMI.
• Cutting-Edge Science: Be on the forefront of applying structural biology and AI to one of the most challenging protein families.
• Startup Culture: An agile, collaborative, high-energy environment with the opportunity to shape the company's culture and direction from the ground up.