Postdoctoral Fellow (Cheminformatics/AI-ML at NCATS)

Office of Intramural Training & Education; Bethesda (MD); On-site; USD 60,000 - 75,000; Full time

Job summary

NCATS, the NIH National Center for Advancing Translational Sciences, Bethesda, MD and surrounding area, seeks a computational chemist/cheminformatics postdoctoral fellow to work at the interface of AI/ML, HTS, and therapeutic discovery.

The selected fellow will join the Therapeutic Development Branch, collaborating with Wei Zheng and Min Shen, and will apply AI/ML, docking, dynamics, and virtual screening to design and develop new therapeutic agents.

Qualifications

• Ph.D. in computational chemistry, cheminformatics, computer science, data science, bioengineering, pharmacology or related discipline.

Responsibilities

• Develop and implement AI/ML models to predict compound activity and properties relevant to drug discovery.
• Conduct structure-based and ligand-based drug design studies to identify novel bioactive compounds.
• Apply molecular docking, molecular dynamics and free-energy calculations to assess binding and stability.
• Perform virtual screening of large chemical libraries for prospective testing.
• Analyze HTS and SAR data to guide hit prioritization.
• Collaborate with experimental scientists to guide synthesis and biological testing.
• Present findings in meetings and at conferences; contribute to publications.

Skills

AI/ML models

Python

Data-driven research

Drug design

QSAR modeling

Education

PhD in computational chemistry/cheminformatics/computer science

Tools

Molecular docking

Molecular dynamics

Virtual screening

Python

Job description

Postdoctoral Fellow (Cheminformatics/AI-ML at NCATS)

Organization

NCATS, Bethesda, MD and surrounding area

Scientific focus area

Chemical Biology,Molecular Pharmacology,Computational Biology

The NIH National Center for Advancing Translational Sciences, Division of Preclinical Innovation, seeks a qualified postdoctoral fellow to conduct interdisciplinary research at the interface of cheminformatics, AI/machine learning, high-throughput screening (HTS), and therapeutic discovery.

About the position

NCATS, a major translational research component of NIH, seeks applications from outstanding candidates to fill a computational chemistry/cheminformatics postdoctoral fellow position in the Therapeutic Development Branch (TDB).

The selected fellow will work under the co-mentorship of Wei Zheng, Ph.D. (Biology Group Leader) and Min Shen, Ph.D. (Informatics Group Leader), in a team environment focused on drug development. The fellow will focus on applying state-of-the art computational chemistry techniques—including molecular modeling, molecular dynamics, artificial intelligence/machine learning (AI/ML) and virtual screening—to help design, identify, and develop new therapeutic agents. The successful candidate will have the opportunity to contribute to high-impact projects and work closely with multidisciplinary teams.

Core Responsibilities

• Develop and implement AI/ML models to predict compound activity, selectivity, and other properties relevant to drug discovery.
• Conduct structure-based and ligand-based drug design studies to identify novel bioactive compounds.
• Apply molecular docking, molecular dynamics and free-energy calculations to assess compound binding and stability.
• Perform virtual screening of large and diverse chemical libraries to identify novel chemotypes for prospective experimental testing.
• Analyze and integrate HTS, dose-response, counterscreen, and follow-up assay data to identify structure-activity relationships (SAR) and guide hit prioritization.
• Work closely with experimental scientists to guide compound synthesis and biological testing based on computational findings.
• Collaborate with researchers internally and externally in other NIH institutes and universities.
• Present research findings in internal meetings and at external scientific conferences and contribute to peer-reviewed publications.

Prospective applicants should possess a Ph.D. in computational chemistry, cheminformatics, computer science, data science, bioengineering, pharmacology or related discipline, with demonstrated experience in data-driven research, including machine learning or statistical modeling.

Strong programming skills in languages such as Python or R are required, along with excellent written and oral communication skills and the ability to work both independently and collaboratively in a multidisciplinary research environment.

Experience working with large-scale biological or chemical datasets, QSAR modeling, or familiarity with AI/ML methods and/or in vitro experimental platforms is preferred.

This position is not eligible for full-time remote work, and NIH does not permit trainees to telework from overseas locations.