Tenure-Track Faculty Positions in Artificial Intelligence and Machine Learning for Drug Discovery

College of Pharmacy, Life Sciences Institute, and Medical School, University of Michigan, Ann Arbor, Michigan

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 2034, 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:

• Michigan Drug Discovery (MDD): A hub for academic-industry partnerships, drug screening, medicinal chemistry, and translational research.
• Broad Campus Collaboration: A Highly collaborative network with faculty from departments like the Department of Pharmacology, Computational medicine and bioinformatics, Michigan Institute for Data Sciences, LSA, and College of engineering.
• Core Facilities: High-throughput screening, medicinal chemistry, structural biology, cryo-electron microscopy, pharmacokinetics, bioinformatics, and AI-driven data analytics.
• Innovation and Commercialization Support: Access to incubator space, business mentoring, venture funding, and technology licensing through Innovation Partnerships.
• AI & Digital Health Innovation: A Presidential initiative providing deidentified multimodal health data, genetic data, data storage and processing, and research implementation services.
• e-HAIL Initiative: A collaboration between Michigan Medicine and the College of Engineering, advancing AI in healthcare and biomedical research. Newly Established U-M and Los Alamos National Laboratory Partnership: A strategic collaboration providing additional computational and experimental resources.