Multiple Ph.D. student positions and PostDoc opportunities starting Fall 2024 are available in new research lab at the University of Central Florida, in the Electrical and Computer Engineering Department and the School of Modeling, Simulation, and Training. Our lab focuses on developing the scientific and engineering foundations of intelligent cyber-physical systems, with applications in autonomous systems. Research areas in our lab include, but are not limited to, scientific machine learning, artificial intelligence, control theory, and optimization. We are engaged in applications such as digital twins, smart buildings & energy systems, autonomous vehicles, and robotics.
Join us in sunny Orlando, Florida, for fulfilling career adventures and growths in science and engineering. Current research initiatives include:
– Physics-informed Machine Learning for Dynamics and Control: Exploring the synergy between machine learning, dynamical systems, control theory, optimization theory, and computer science.
– Integrated Machine Learning and Distributed Optimization: Focusing on the convergence of machine learning, distributed optimization, networking, and communication.
– Learning-based Control and Optimization for Autonomous Vehicles and Robots.
– Mobile Robotic Sensor Networks for Spatiotemporal Fields.
We are seeking applicants with a strong background and research record in control theory, optimization, machine learning/AI, computing/programming, and/or robotics. If you are interested, please send Prof. Truong Nghiem at truong.nghiem@gmail.com an email that includes highlights of your background, experience, and interests, along with your academic CV, transcripts, any test scores (TOEFL, IELTS for international applicants), and any relevant publications or sample code. Only selected applicants will be replied to.
Please note: Due to regulatory restrictions, international applicants not currently residing in the U.S. from certain countries may face limitations. We recommend verifying your eligibility through a quick online search before applying.
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