Assistant Professor in Artificial Intelligence/Machine Learning for Materials Design (tenure-track)

A Ph.D. in Chemistry or a related field (particularly in Materials Chemistry, Inorganic Chemistry, Physical Chemistry, Physical Organic Chemistry, or Analytical Chemistry) is required. Prior teaching experience and familiarity with modern teaching practices are preferred, though all candidates committed to excellence in teaching are encouraged to apply.

The Department of Chemistry at Tufts University invites applications for a tenure-track Assistant Professor position in the area of Artificial Intelligence (AI)/Machine Learning (ML) for Materials Design.

The Chemistry Department at Tufts is a highly-active (R1) research community that values excellence in both education and scholarship, along with collaborative and interdisciplinary research. This position will contribute to the department’s expanding strengths in AI/ML and materials research, in alignment with efforts across the broader University, including the Tufts Institute for Artificial Intelligence and the Tufts Epsilon Materials Institute. For this position, the central research focus should be the development and/or use of AI/ML-based techniques and computational methods to advance design, synthesis, or evaluation of novel materials for applications in energy, biomedicine, or other critical fields. Candidates should demonstrate the potential to establish a productive, independent, and extramurally funded research program.

Teaching responsibilities will include undergraduate and graduate courses in chemistry related to the candidate’s research, particularly in Computational Chemistry, AI/ML, Materials Chemistry, Inorganic Chemistry or Physical Chemistry., Tufts University, founded in 1852, prioritizes quality teaching, highly competitive basic and applied research, and a commitment to active citizenship locally, regionally, and globally.