Tenure-Track Faculty Position(s) in Artificial Intelligence and Machine Learning for Drug Discovery

Summary

The University of Michigan (U-M) invites applications for three tenure-track faculty positions in the area of Artificial Intelligence (AI) and Machine Learning (ML) in Drug Discovery. This is a unique cluster hire initiative spanning the College of Pharmacy, Life Sciences Institute (LSI), and Medical School. We welcome applications from both early and mid-career candidates with strong records of research excellence in AI / ML-driven approaches to drug discovery.

Successful candidates will be appointed within the unit most appropriate to their expertise while fostering interdisciplinary collaborations across the university.

Strategic Impact and Vision

This cluster hire aligns with U-M's Vision , emphasizing :

• Research Innovation : Advancing AI / ML methodologies for drug discovery and improving therapeutic success rates.
• Interdisciplinary Collaboration : Strengthening connections between computational and experimental drug development experts.
• Economic and Societal Impact : Translating discoveries into startup ventures and industry partnerships to drive drug commercialization.
• Education and Workforce Development : Training the next generation of scientists in AI / ML-enabled drug development.

About the Positions

Drug development faces significant challenges, including high costs, long timelines, and a 90% failure rate in clinical trials. AI and ML have the potential to enhance drug discovery by improving the identification of disease and drug targets, accelerating the identification of drug candidates, optimizing the design of therapeutics, and guiding predictions of clinical outcomes. The goal of this cluster hire is to advance U-M?s leadership in drug discovery by integrating cutting-edge AI and ML methodologies into the drug discovery process, enhancing efficiency, reducing failure rates, and supporting therapeutic innovation.

Resources and Collaborative Environment

U-M provides an exceptionally collaborative and resource-rich environment for AI / ML and drug discovery research, including :

Responsibilities

Requirements

Modes of Work

Positions that are eligible for hybrid or mobile / remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.