Post-Doctoral Fellow - GZhou Lab

The Wistar Institute • Philadelphia, PA

22h • Onsite

About The Position

The Wistar Institute is recruiting a Post-Doctoral Fellow to work in the laboratory of Dr. Guangfeng Zhou as part of the Center for Advanced Therapeutics (CAT) at The Wistar Institute. The Zhou lab develops physics-based and AI-based computational methods to accelerate therapeutic discovery. His current program focuses on developing AI-based and physics-based computational approaches for drug discovery, including models that integrate physical and chemical principles, docking and binding-affinity prediction methods, and AI-accelerated virtual-screening platforms to identify and prioritize promising therapeutic leads. We are seeking a highly motivated Post-Doctoral Fellow interested in developing and applying AI and physics-based computational methods for drug discovery. The successful candidate will have opportunities to pursue projects spanning AI model development, protein-ligand modeling, molecular docking and binding-affinity prediction, and large-scale virtual screening. The candidate will also have opportunities to work closely with experimental collaborators to apply newly developed computational methods to challenging therapeutic targets and experimentally validate computational predictions.

Requirements

• Nearing completion of or already have a PhD in computational chemistry, biophysics, computer science, or a related field.
• Strong computational background.
• At least one first-author peer-reviewed publication.
• Creative, self-motivated, and interested in developing new computational methods.
• Ability to work collaboratively with computational and experimental researchers.

Nice To Haves

• Machine learning/deep learning
• Molecular modeling
• Molecular dynamics
• Protein structure modeling
• Cheminformatics
• Computational drug discovery

Responsibilities

• Developing and applying AI and physics-based computational methods for drug discovery.
• Pursuing projects spanning AI model development, protein-ligand modeling, molecular docking and binding-affinity prediction, and large-scale virtual screening.
• Working closely with experimental collaborators to apply newly developed computational methods to challenging therapeutic targets.
• Experimentally validating computational predictions.

Benefits

• Competitive salary
• Excellent benefits package

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: Ph.D. or professional degree