Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
-
multi-agent autonomous systems and related technologies. This will include development of distributed monitoring algorithms enabling agents in a multi-agent swarm to autonomously locate other agents in
-
processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
-
), Machine Learning on Quantum Computers, Security of Quantum Circuits, Design Automation and Tools for Quantum Circuits, Robust and Efficient Mapping of Quantum Algorithms on Quantum Machines, Quantum Noise
-
models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental
-
of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or experimental means. The PDA is expected to actively disseminate results through publications in
-
inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic
-
others (but not limited to): Computer Organization and Architecture, Data Structures and Algorithms, Computer Programming for Engineers, Object Oriented Programming, Digital Logic and Advanced Digital
-
. The Department of Robotics focus is on rigorous, high-impact, original research emphasizing robot learning, (eg CoRL) and robot algorithms (eg WAFR) rather than development of new robot hardware. Research topics
-
innovative ML/AI algorithms for time series with chaotic shocks and contribute to the team’s research on autonomous vehicle security. Applicants must have a Ph.D. degree (or equivalent) in applied mathematics