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The University of Texas at Austin invites applications for a tenure-track Assistant Professor in Neuroscience with a focus on computational neuroscience. The ideal candidate will bridge neuroscience with artificial intelligence, machine learning, and related computational sciences.
Candidates with interests in brain-computer interfaces, computational psychiatry, and precision neuroscience are welcome to apply. Applicants must have a Ph.D.
The Department of Neuroscience at The University of Texas at Austin invites applications for a tenure-track faculty member at the rank of Assistant Professor, who is working in the area of computational neuroscience and motivated to become an influential researcher, educator, and contributor to the scholarly community.
The Department is seeking candidates involved in computational/theoretical approaches that bridge the gap between neuroscience and artificial intelligence, machine learning, and other areas of computational sciences. We are seeking a new colleague whose work will synergize with our faculty engaged in cellular/molecular, cognitive/behavioral, and systems neuroscience. Other areas of interest include, but are not limited to, brain-computer interfaces, computational psychiatry, and other links to precision medicine and neuroscience research.
The University of Texas at Austin has strong and interactive research programs in Neuroscience, Psychology, Computer and Computational Science, Statistics, Mathematics, Engineering, Physics, Chemistry, and Molecular Biology, with an established culture of cross disciplinary collaboration.
The position requires a Ph.D. or equivalent degree with training in computer science, neuroscience, or a related field.
Inquiries can be directed to Dr. Michael Mauk (mike@mail.clm.utexas.edu), Department of Neuroscience.
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.