"Open Rank Tenure System Faculty Position in Computational Neuroscience"

Job Summary

Position Description

The Department of Neuroscience at The University of Texas at Dallas seeks to hire a tenure system faculty member (open rank) whose research program combines computational (dry lab) approaches with experimental wet lab techniques, the latter potentially including cellular, tissue, or non-behavioral animal models. Candidates should have expertise in neural coding, neural computation, neural control, or using approaches at the intersection of neuroscience and artificial intelligence as part of a computational neuroscience hiring initiative. The goal of this initiative is to develop an internationally recognized computational neuroscience research and educational program at UT Dallas that leverages and extends existing University expertise in systems and cognitive neuroscience, neural device development, and machine learning. The ideal candidate would conduct highly collaborative research in areas of focus aligned with Department strengths in Learning & Memory, Decision Making, Motor Control, Sensory Perception and Pain, or Neurogenomics. The new faculty member would be expected to teach undergraduate and graduate courses related to their area of expertise.

The appointment commences for the fall 2026 semester.

Qualifications

Minimum Education and Experience: A PhD or equivalent in Neuroscience, Computer Science, Mathematics, or a related field is required prior to employment. Candidates should demonstrate commitment to excellence in teaching, research, and service and evidence of an innovative and productive research program with (at the Assistant Professor rank) clear potential for funding. Applicants for Associate or full Professor appointments should have track records of research productivity and funding commensurate with those ranks. Candidates are expected to demonstrate the ability to work effectively in a highly collaborative, engaging, and dynamic environment comprised of individuals with a range of backgrounds, skills, and perspectives. We are seeking candidates able to produce research and scholarly or creative achievements that enhance the program and the discipline, and able to deliver high quality teaching using evidence-based practices to effectively engage students from a range of backgrounds and experiences.

Preferred Education and Experience: In addition to a PhD degree, competitive candidates at the Assistant Professor rank would have postdoctoral training and robust publication records, and evidence of a dynamic and productive research program with clear potential for funding.

UT Dallas School of Behavioral and Brain Sciences and the Department of Neuroscience

The University of Texas at Dallas is a Carnegie R1 Research Institution and is among the fastest growing universities in the nation. The School of Behavioral and Brain Sciences (BBS) is one of seven schools at UT Dallas and is ranked 2nd in total new research grants and research expenditures over the past year. [Detailed description of BBS and Department of Neuroscience...]

Application Instructions

Applicants should upload the following:

• Cover letter and full curriculum vitae summarizing their interests and their qualifications for the position.
• Statement of teaching philosophy describing their conceptualizations of teaching and learning, and teaching and assessment methods, and how their teaching practices will engage students from a range of backgrounds and experiences.
• A writing/publication sample.
• Full contact information for at least three academic or professional references.

Priority will be given to completed applications received by January 15, 2026. Reviews will continue until the position is filled or the search is closed on February 28, 2026.

Minimum Qualifications

An earned graduate degree appropriate to the academic discipline and a record of productivity and professional achievement.

Preferred Education and Experience

Ph.D. in Neuroscience, Computer Science, Mathematics, or a related field, Postdoctoral Fellowship training, and evidence of a dynamic and productive research program with clear potential for funding.