Asst Professor - Electrical Engineering & Computer Science

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At the University of Wyoming, we value our employees and invest in their success. Our comprehensive benefits package is designed to support your health, financial security, and work‑life balance.

Generous Retirement Contributions
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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
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Enjoy access to medical, dental, and vision insurance with competitive employer contributions, that include 4 deductible options to suit your needs.

Paid Time Off
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Benefit from ample vacation, sick leave, paid holidays, and paid winter closure.

Tuition Waiver
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Employees and eligible dependents can take advantage of tuition waivers, supporting continuous education and professional growth.

Wellness and Employee Assistance Programs
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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.

Assistant Professor

The Department of Electrical Engineering and Computer Science (EECS) invites applications for tenure‑track faculty in Computer Science at the rank of Assistant Professor with an anticipated start date of August 25, 2026. We encourage applications from outstanding candidates in the area of artificial intelligence and machine learning. Applicants must hold a Ph.D. in Computer Science or a closely related field by the date of employment.

This position will remain open until filled. Complete applications received by 12/01/2025 will receive full consideration.

• Foundational and Theoretical Methods in AI/ML
  • Learning Theory and Control Theory in AI;
    Optimization for AI/ML Models (convex, non‑convex, stochastic, robust);
    Probabilistic and Statistical Methods (variational inference, causal inference, Gaussian processes);
    Computationally Efficient Learning;
    Algorithmic Game Theory and Decision Theory
• AI/ML Algorithms and Model Development
  • Development of novel AI/ML Algorithms (foundation models, large language models, neural networks, generative models);
    Reinforcement Learning (decision‑making, control, planning, hierarchical RL);
    Deep Learning;
    Adversarial Learning and Machine Unlearning
• AI/ML Architectures and Infrastructure
  • Development of novel AI/ML Architectures;
    Training Infrastructure;
    Decision‑Support Tools;
    Advanced Cyberinfrastructure for AI and Intelligent Systems;
    Multi‑Agent Systems

While we primarily seek expertise in core areas of AI/ML, we welcome scholars with expertise in other areas of AI/ML to apply, such as, but not limited to:

• Explainable, Responsible and Trustworthy AI
  • Causality, Fairness, and Accountability;
    Model Bias, Interpretability, and Explainability;
    Authenticity and Trust in AI Systems;
    Federated and Decentralized Learning;
    Privacy‑Aware AI
• Human‑Centered AI
  • Human Factors in AI, Human‑AI Interfaces;
    Natural Language Processing, Agents, and Interactive AI

Successful candidates are expected to develop and maintain a strong research program and work with colleagues in the department to develop educational and research in Artificial Intelligence and Machine Learning.

The successful candidates’ responsibilities will include developing a vigorous independent research program supported by external grant funding, high‑quality teaching of EECS courses, mentoring of graduate students; working collaboratively with faculty and staff, and service to the university and state.

• Doctorate degree in Computer Science or a closely related field by date of appointment.
• Excellent…