Minimum Qualifications:
A terminal doctoral degree (PhD or equivalent) in neuroscience, biological sciences, or related field from a college or University accredited by the US Department of Education or internationally recognized accrediting organization August 15, 2026.A record of research and scholarly activity in systems neuroscience or fields directly related to the position description, as demonstrated by peer-reviewed publications, preprint manuscripts, books, or conference proceedings.The ability and a plan to effectively teach undergraduate and graduate level coursesExperience working with interdisciplinary teamsApplicants must demonstrate an ability to develop inclusive and equitable relationships within our diverse campus communityApplicants must demonstrate an ability to support diversity, equity, access, inclusion, and belonging relative to their role Preferred Qualifications:
Demonstrated experience in using quantitative approaches (broadly defined), computational modeling, artificial intelligence (AI), machine learning, or similar tools in the field of systems neuroscience (or related discipline)A record of innovation in quantitative systems neuroscience, which includes peer-reviewed publications in impactful journalsExperience using modern neuroscience methodologies to drive innovative research directionsEvidence of potential for securing extramural funding for research and creative activitiesExperience in teaching and curriculum development at the collegiate level Working Environment:
Typical office, classroom, and scientific research lab environments