Assistant Professor - AI-enabled Drug Discovery & Translation

campaign overseen by central University leadership and designed to recruit a large cohort of convergence research faculty working in health, energy, sustainability, and security. Competitive candidates are expected to hold a Ph.D. or equivalent degree by the start of the appointment and demonstrate the potential for exceptional research and excellence in teaching and service. The successful candidate will be appointed at the rank of Assistant Professor. Description of the position: We seek candidates who will establish nationally recognized, externally funded research programs in biomolecular engineering addressing grand challenges in AI-enabled drug discovery. The convergence of artificial intelligence and machine learning, computational chemistry, molecular modeling, structural biology, robotics, and laboratory automation is fundamentally transforming the pharmaceutical discovery and development process. These advances have the potential to dramatically reduce the time, cost, and risk associated with identifying and optimizing new therapeutic candidates. AI-driven molecular design, predictive modeling, virtual screening, digital twins of biological systems, and autonomous laboratories are creating an integrated discovery paradigm in which promising drug candidates can be rapidly designed, synthesized, characterized, tested, and iteratively optimized. By tightly coupling computational prediction with automated experimentation and high-throughput validation, these technologies enable the exploration of chemical and biological design spaces at a scale and speed that were previously unattainable. AI-enabled drug discovery therefore represents one of the most rapidly advancing and potentially transformative frontiers in modern biomolecular engineering, with profound opportunities to accelerate the development of next-generation therapeutics and improve human health. We welcome applications from candidates working across a broad spectrum of AI-assisted drug discovery methodologies. Key areas of interest include, but are not limited to: • Therapeutic Discovery & Screening: Novel AI frameworks for the discovery and optimization of small-molecule therapeutics, biologics, and peptide-based drugs. • Multi-Omic Integration: Advanced machine learning architectures for integrating genomic, transcriptomic, and proteomic data to identify actionable therapeutic targets. • Next-Generation Modalities: Computational design of RNA- and gene-based therapeutics. • Precision & Personalized Medicine: AI-driven platforms targeting cancer, infectious diseases, neurological disorders, cardiovascular disease, and rare genetic conditions. Expertise in cancer-related research would be particularly desirable because it would maximize opportunities for collaboration with researchers working at the forefront of the field at UH and the nearby Texas Medical Center, the largest medical complex in the world. The Department has 26 tenured and tenure-track faculty, modern research facilities, annual research expenditures exceeding $12 million, and a vibrant graduate program with more than 100 Ph.D. students. The successful candidate will join a collegial group of research-oriented faculty working in a highly collaborative environment and will become a member of the prestigious Presidential Frontier Faculty network of scholars at UH. UH is a Carnegie Tier 1 public research university and is home to several research centers and institutes that provide opportunities for collaborative research, including the UH Drug Discovery Institute, the UH Hewlett Packard Enterprise Data Science Institute, the Center for Nuclear Receptors and Cell Signaling, and the recently awarded $44.2 million Consortium for Translational and Precision Health between UH and Baylor College of Medicine, among others. The successful candidate will also have access to state-of-the-art shared core facilities at UH and the Texas Medical Center. The Houston metropolitan area offers an excellent quality of life and a vibrant arts and entertainment scene supported by a growing economy. Houston is home to the Texas Medical Center and has a broad industrial base in energy, chemicals, materials, aeronautics, and medical technologies, offering additional opportunities for collaborative research. Houston has recently attracted multibillion-dollar investments in drug manufacturing facilities from two major pharmaceutical companies. A complete application consists of: (1) a cover letter; (2) a curriculum vitae; (3) a detailed description of research interests (not to exceed 5 pages); (4) a statement of education discussing teaching interests, teaching experience, and mentoring experience (not to exceed 2 pages); (5) three representative publications; and (6) the names and contact information (email addresses and phone numbers) of three professional references whom we may contact. Review of applications will begin on November 15, 2026, and will continue until the position is filled. The position is available effective Fall 2027. For more information please contact the appropriate Search Committee Chair: Professor Navin Varadarajan William A. Brookshire Department of Chemical & Biomolecular Engineering http://www.chee.uh.edu/ E-mail: chbefacultysearch@egr.uh.edu Employees are expected to have a home address in the state of Texas for the duration of their appointments. Official transcripts are required for a faculty appointment and will be requested upon selection of the final candidates. All positions at the University of Houston-System are security sensitive and will require a criminal history check. Individuals conducting research in critical infrastructure areas (i.e., communication infrastructure systems, cybersecurity systems, electric grid, hazardous waste treatment systems, and/or water treatment facilities) are subject to regular review to ensure the security and integrity of the research is maintained. The University of Houston System and its universities are Equal Opportunity Institutions. Everyone is encouraged to apply.