Publisher
source

Gilead Sciences

Postdoctoral Scientist in Structural Biology, Chemistry, and AI/ML for Small Molecule Drug Discovery Gilead Sciences in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Three-year fixed-term postdoctoral position at Gilead. The post describes a postdoctoral training program but does not specify stipend, salary, tuition, or other financial details.

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Country

United States

University

Gilead Sciences

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Keywords

Computer Science
Chemistry
Biomedical Engineering
Biology
Structural Biology
Computational Chemistry
Pharmacy
Chemoinformatics
Virtual Screening
ML

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About this position

Postdoctoral Scientist, Structural Biology and Chemistry at Gilead Sciences in Foster City, California, United States.

This is a three-year fixed-term postdoctoral position in the Structural Biology and Chemistry department, focused on AI/ML for Small Molecule Drug Discovery. The successful candidate will join the Computational Modeling Group and work on evaluating and developing machine learning tools for drug discovery workflows.

Research areas and keywords: structural biology, chemistry, AI/ML, computational chemistry, cheminformatics, virtual screening, ADME modeling, potency prediction, hit identification, hit-to-lead, lead optimization, heterobifunctional degraders, uncertainty quantification, applicability domain assessment.

Core responsibilities include assessing co-folding tools, potency models, and ADME models using historical Gilead data and structures; implementing methods for virtual screening of ultra-large libraries; exploring active learning and Thompson sampling; and investigating ML approaches for predicting properties of heterobifunctional degraders from SMILES or 3D conformational ensembles.

Eligibility highlights: Ph.D. required. The post seeks candidates with deep expertise in AI/ML applied to drug discovery and/or computational chemistry, strong Python and ML framework skills, and experience with cheminformatics toolkits such as RDKit, OpenEye, or Schrodinger. Strong communication, critical thinking, independence, and organizational skills are emphasized.

Funding: The posting confirms a postdoctoral training program and fixed-term appointment, but does not provide stipend or salary details.

Location: Onsite in Foster City, California, United States.

How to apply: Use the Workday application page linked in the posting. Current Gilead employees and contractors should apply through the Internal Career Opportunities portal in Workday.

Funding details

Three-year fixed-term postdoctoral position at Gilead. The post describes a postdoctoral training program but does not specify stipend, salary, tuition, or other financial details.

What's required

Ph.D. required, with 0+ years of relevant research experience. Deep expertise in AI/ML as applied to drug discovery and/or computational chemistry is required. Candidates should have knowledge of machine learning architectures relevant to chemistry and structural biology, strong Python programming skills, proficiency with ML frameworks, and the ability to design and evaluate robust validation strategies including uncertainty quantification and applicability domain assessment. Experience with cheminformatics toolkits such as RDKit, OpenEye, or Schrodinger is desired. Excellent communication, interpersonal, critical thinking, creativity, independence, and organizational skills are expected.

How to apply

Apply through the Gilead careers Workday posting using the Apply button on the job page. Current Gilead employees and contractors should apply via the Internal Career Opportunities portal in Workday.

More information can be found here

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