Asst​/Assoc Professor - Applied AI​/ML and Advanced AI

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• Generous Retirement Contributions:
  The State contributes 14.94% of your gross salary, and you contribute 3.68%, totaling 18.62% toward your retirement plan.
• Exceptional Health & Prescription Coverage:
  Enjoy access to medical, dental, and vision insurance with competitive employer contributions, that include 4 deductible options to suit your needs.
• Paid Time Off:
  Benefit from ample vacation, sick leave, paid holidays, and paid winter closure.
• Tuition Waiver:
  Employees and eligible dependents can take advantage of tuition waivers, supporting continuous education and professional growth.
• Wellness and Employee Assistance Programs:
  Stay healthy with wellness initiatives, counseling services, and mental health resources.

At the University of Wyoming
, we are committed to creating a supportive and enriching workplace. To learn more about what we offer, please refer to UW's Benefits Summary.

Tenure-Track Assistant/Associate Professor Positions in Applied AI/ML and Advanced AI Applications

As part of the University of Wyoming's (UW's) AI Strategic Initiative and the President's AI Across the University Commission, UW invites applications for three (3) tenure-track Assistant/Associate Professor positions in applied artificial intelligence (AI), machine learning (ML), and advanced applications of AI. We seek faculty who will build collaborative research programs, secure significant external research funding, and create impactful learning experiences for students.

For a position designated at the Assistant Professor rank, candidates must demonstrate strong potential to build a nationally recognized, externally supported research program. For positions designated at the Associate Professor rank, candidates are expected to have a nationally recognized, established record of scholarship, external research funding and leadership. We welcome candidates from academic, applied, and interdisciplinary backgrounds, including those with experience in industry, national laboratories, government, or community-engaged settings, particularly where AI/ML connects to real-world impact.

UW is a research university with twelve colleges and schools enrolling approximately 11,000 students. The University prides itself on research innovation, teaching excellence, industrial engagement, and statewide impact. Faculty have access to state-of-the-art facilities and major cyberinfrastructure investments, including the Advanced Research Computing Center (ARCC), the NCAR-Wyoming Supercomputing Center (NWSC), GPU computing resources, and dedicated funding to support research growth. In addition, candidates with energy-related expertise may qualify for funding support from the School of Energy Resources.

As Part Of This University-wide Commitment To AI Advancement, UW Is Conducting a Multi-department AI Faculty Cluster Hire To Recruit Scholars Who Will Join UW's Expanding Community Of Researchers Applying AI And Data-intensive Methods To Scientific, Engineering, Societal, And Translational Challenges. This Cluster Will Support Research And Teaching Across Strategically Important Domains In The Partnering Academic Units

• Chemistry
• Chemical Engineering
• Electrical Engineering and Computer Science
• Energy & Petroleum Engineering
• Mathematics & Statistics
• Physics & Astronomy
• School of Computing
• School of Energy Resources

• STEM applications:
  Applied AI/ML across partnering unit disciplines, with particular interest in energy systems (including nuclear, subsurface, petroleum, and advanced energy technologies), materials research, condensed matter physics, process engineering and control, critical minerals, quantum information sciences and engineering, cybersecurity and blockchain, and controlled-environment agriculture.
• AI and Scientific Computing:
  Research and tool development at the intersection of artificial intelligence and scientific computing including physics-informed neural networks and digital twins; uncertainty quantification, high-dimensional data analysis, and visualization; generative models for scientific discovery; integration of HPC and AI and AI-enhanced numerical methods; explainable and trustworthy AI for STEM applications; and mathematically grounded approaches applied in STEM contexts, such as geometric and topological ML, neural ODEs/PDEs, reduced-order modeling, structure-preserving ML/AI, and optimization.

• Two (2) positions jointly appointed in the…