Assistant Professor in Pharmaceutical Sciences

Department of Pharmaceutical Sciences

College of Pharmacy

University of Michigan

The Department of Pharmaceutical Sciences in the University of Michigan (UM) College of Pharmacy seeks outstanding candidates for a tenure-track faculty position at the rank of Assistant Professor. We are seeking an innovative scientist who will establish a nationally recognized, externally funded research program that complements and expands the department's strengths in pharmaceutical sciences.

As part of a new faculty cluster hire, this position is supported in partnership with the Michigan Program for Advancing Cultural Transformation (M-PACT), which seeks to build a sustainable scientific community that strengthens the capacity of those who serve as catalysts for change in academic and healthcare environments. M-PACT is funded in part by a grant from the National Institutes of Health.

M-PACT is a state-of-the-art faculty development program for new tenure-track faculty with a demonstrated and ongoing commitment to advancing issues of diversity, equity, access, and inclusion in the health sciences.

The successful candidate will have 75% protected research time for their first 5 years and will be expected to build an independent, externally funded research program. Teaching and service expectations will be defined in collaboration with the Department Chair. Candidates should demonstrate the potential for or experience with leadership in research and professional activities, including publication, research funding, participation in collaborative and interdisciplinary initiatives, and service to the College, University, and broader academic community.

They must be able to articulate how their research, teaching, and/or service activities will support the College's mission.

The University of Michigan offers an exceptional environment for computational and data-driven pharmaceutical sciences. Faculty benefit from world-class resources in artificial intelligence, machine learning, high-performance computing, and biomedical informatics, including the Great Lakes and ARMIS high-performance computing cluster and expanding AI computing infrastructure. Collaborative opportunities span the College of Pharmacy, Michigan Medicine, the Medical School, College of Engineering, School of Public Health, and campus-wide initiatives in AI and Precision Health.

Investigators have access to extensive clinical, genomic, imaging, and real-world health datasets, enabling interdisciplinary research in computational biology, drug discovery, translational science, and precision therapeutics.

We invite applications from exceptional investigators whose research advances pharmaceutical sciences through computational, quantitative, and data-driven approaches. Areas of interest include, but are not limited to:

• Computational (AI, machine learning) approaches to drug discovery, engineering, and development.
  • Small-molecule therapeutics.
  • Peptides and protein therapeutics.
  • Nucleic acid medicine.
  • Cell & gene therapies, and other next-generation therapeutics.
• Computational approaches to the development of drug formulations and delivery systems.
  • Drug formulations and drug delivery systems: AI- and machine learning-enabled design of formulations and drug delivery systems for small molecules, biologics, nucleic acids, and advanced therapeutics.
  • Biopharmaceutical performance:
    Mechanistic and data-driven modeling of drug release, transport, absorption, biodistribution, and pharmacokinetics.
  • Digital pharmaceutics: AI, digital twins, and model-informed approaches for formulation development, manufacturing, and quality by design (QbD).
• Pharmacokinetic/pharmacodynamic (PK/PD) modeling and simulation.
  • PK/PD modeling and simulation for drug development and precision dosing.
  • Quantitative analysis of exposure?response relationships and therapeutic optimization.
  • Model-informed strategies integrating preclinical and clinical data for translational medicine.
• Pharmacometrics, quantitative systems pharmacology, and model-informed drug development (MIDD).

Applicants whose research integrates computational methods with experimental, translational, or clinical pharmaceutical sciences are particularly encouraged to apply. Candidates are expected to develop innovative methodologies that accelerate therapeutic discovery, optimize drug development, improve regulatory decision-making, and ultimately enhance patient outcomes.

• A Ph.D. (or…