Description

The San Diego State University Department of Chemistry and Biochemistry seeks to hire a tenure-track assistant professor with expertise in AI-enabled Chemical Discovery, broadly defined.  We seek candidates employing cutting-edge interdisciplinary approaches developing artificial intelligence applications for chemical questions. Relevant AI-enabling research areas may include, but are not limited to, reaction discovery and optimization, synthesis planning, catalyst and reagent design, mechanistic analysis, and prediction or control of chemical reactivity and selectivity; molecular and biomolecular structure, function, and design, including generative design of biological systems; chemical biology; and the discovery of functional molecules and materials. Approaches integrating AI with experimental chemistry, automated or closed-loop experimentation, chemical theory, or simulation are encouraged. Applicants from anywhere within the chemical science continuum are invited, as long as the development of AI-enabled approaches is a central focus.  Apply by October 22, 2026.

Requirements

Required qualifications by date of application

• A strong record of original research achievements, along with demonstrated ability to: (a) establish and sustain a vigorous, independent, and externally funded research program; (b) effectively teach both undergraduate and graduate courses; and (c) actively contribute to service activities within the university and the broader professional community.
• Demonstration of past accomplishments and/or future plans in at least three (3) of the “Building on Inclusive Excellence” criteria (https://fs-diversity.sdsu.edu/recruitment/guidance-candidates).

Required qualifications by date of hire:

• Terminal degree in Chemistry, Biochemistry, Computer Science or a closely related field, with all degree requirements met.

Preferred qualifications:

• Postdoctoral or equivalent research experience.
• Demonstrated expertise in developing or substantively integrating artificial intelligence, machine-learning, or data-driven methods to address chemical or biochemical questions.
• A research program that combines methodological innovation with chemically or biochemically meaningful discovery and validation.
• Potential to build interdisciplinary collaborations across experimental, computational, and theoretical research areas.
• Evidence of effective teaching or mentoring in chemistry, biochemistry, computation, data science, or related disciplines.