Postdoctoral Scholar

Tufts University • UNAVAILABLE, Idaho

1d • Remote

About The Position

The Cummings School of Veterinary Medicine at Tufts University is seeking a highly motivated Postdoctoral Research Associate to develop AI-driven approaches to drug discovery under the supervision of Dr. Marvin Schulte, Associate Dean for Graduate Education. This position will focus on utilizing large and small molecular databases, explainable AI (XAI), and generative AI to identify and optimize modulators of neuronal nicotinic acetylcholine receptors (nAChRs) based on existing data. This is a part-time position, a 6-month limited-term role, and has the ability to be remote.

Requirements

• Ph.D. (or completion of all Ph.D. requirements, including dissertation defense) in computational chemistry, bioinformatics, pharmacology, neuroscience, biomedical engineering, or a related field.
• Experience with AI/ML applications in drug discovery, including database curation, model training, and validation.
• Hands-on experience in experimental laboratory techniques relevant to drug development and receptor biology.
• Strong programming skills in Python, R, or similar languages for AI/ML
• Familiarity with structure-activity relationship (SAR) analysis, molecular docking, and cheminformatics tools.
• Understanding challenges and modern approaches in drug discovery and receptor
• Ability to work independently while collaborating effectively with interdisciplinary teams.

Nice To Haves

• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
• Background in molecular dynamics simulations or electrophysiological
• Prior research on nAChRs or other ion channels
• Strong publication record in relevant areas.

Responsibilities

• Develop AI-based models for virtual screening, molecular design, and lead optimization targeting nAChRs.
• Integrate large public datasets and small experimental datasets to improve predictive accuracy.
• Implement explainable AI techniques to enhance model interpretability and guide medicinal chemistry efforts.
• Utilize generative AI approaches to design novel drug-like compounds with improved pharmacological profiles.
• Validate computational predictions through experimental techniques, including receptor assays.
• Collaborate with interdisciplinary teams, including medicinal chemists and electrophysiologists, to refine drug candidates.
• Publish findings in peer-reviewed journals and present at conferences.

What This Job Offers

• Job Type: Part-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree