The Walker Department of Mechanical Engineering at The University of Texas at Austin seeks applicants for multiple positions. Candidates with expertise in the following research areas are of the most interest to the Department. (Candidates should view these areas of emphasis in the broadest sense in determining whether they match their research skills and interests.)
NUCLEAR ENGINEERING, with an emphasis on nuclear materials or radiochemistry. Candidates should be able to demonstrate an ability to teach both nuclear engineering and materials science or mechanical engineering courses at the undergraduate level.
ROBOTICS & PHYSICAL AI, with an emphasis on embodied autonomous and semi-autonomous systems that perceive, plan, and act under real-world physical constraints, including in close collaboration with humans, spanning: (a) novel actuator and sensor design, including soft and smart materials and metamaterials, and their integration into robotic systems; (b) physics-inspired machine learning for perception, planning, and control, together with the experimental data collection and simulation tools needed to support it, with a balanced approach to theory and experimental work; (c) applications in assistive and rehabilitation robotics that restore, augment, or support human motor, sensory, or cognitive function, including emerging brain-robot interfaces, and in intelligent automation for complex, unstructured industrial, service, or medical environments.
ADVANCED MANUFACTURING, with an emphasis on advancing additive manufacturing as a production technology for aerospace, defense, and other critical applications. Research may span the technologies needed to make additive manufacturing more intelligent, predictable, and certifiable, including machine-learning-enabled process control, in situ sensing and monitoring, data-driven and physics-based modeling, digital twins, materials-by-design, and integrated process-structure-property relationships. Of particular interest are candidates whose work can reduce the time and cost associated with process and part qualification by moving quality assurance from post-build inspection to predictive, in-process understanding and control. The successful candidate will strengthen UT Austin's leadership in production-focused additive manufacturing and advance the field toward reliable, autonomous processes.
Candidates at the rank of Assistant Professor are sought for the Nuclear and Robotics searches. In the Advanced Manufacturing search applications are welcomed at both the Assistant Professor and Tenured Associate/Full Professor ranks.
