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/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
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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
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inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic
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. 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
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research interests might be considered, priority will be given to those able to relate to one or more of the above topics. Applicants must have a PhD in Mathematics, Statistics or Computer Science obtained
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collaborators. Qualifications Applicants must hold a PhD degree in electrical/electronics engineering, telecommunications or related field. Other requirements include Expertise in several areas among
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Information Theory. While excellent candidates with other research interests might be considered, priority will be given to those able to relate to one or more of the above topics. Applicants must have a PhD in
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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
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have a PhD in Civil Engineering, Engineering Mechanics, or Mechanical Engineering. Applicants are expected to demonstrate research experience in the fields of structural modeling and machine-learning
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immediately with a flexible start date, initially for 1 year with the possibility of renewal based on performance. The ideal candidate is self-motivated and hard-working with a PhD in synthetic biology