Post Doc Scientist, Structural Biology and Chemistry
On-siteFoster City, California, United States
Job Summary
Conduct detailed evaluation and analysis of AI tools and ML models impacting Small Molecule Drug Discovery from hit identification through lead optimization. Utilize historical Gilead data and structures to assess co-folding, potency, and ADME models alongside Computational Chemists and AI/ML Scientists. Implement methods enabling virtual screening of ultra-large libraries via Active Learning and Thompson Sampling, and investigate ML feasibility for predicting properties of heterobifunctional degraders. Present findings through internal and external communications and publish in high-impact journals. This three-year fixed-term postdoctoral training program places the candidate within the Computational Modeling Group, leveraging cutting-edge AI/ML technologies to support Gilead's structural biology and chemistry objectives.
Required Qualifications
- Ph.D.
- 0+ years of relevant research experience with deep expertise in AI/ML as applied to drug discovery and/or in Computational Chemistry
- Knowledge of machine learning architectures relevant to chemistry and structural biology
- Strong programming skills in Python and proficiency with ML frameworks
- Ability to design, implement and evaluate robust model validation strategies, including uncertainty quantification and applicability domain assessment
- Excellent communication skills (both verbal and technical) and interpersonal skills
- Must think critically and creatively
- Ability to work independently
- Ability to determine appropriate resources for resolution of problems
- Strong organizational and planning skills
- This is a three year fixed-term postdoctoral position
Desired Qualifications
- Expertise with cheminformatics toolkits such as RDKit, OpenEye or Schrodinger
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