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Field
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of robots to interact with the surrounding environment and humans during the execution of specific tasks. Project description The fundamental vision of RAI is aiming in closing the gap from theory to real
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of robots to interact with the surrounding environment and humans during the execution of specific tasks. Project description The vision of RAI is aiming in closing the gap from theory to real life, while
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opportunities for collaboration with others and learning about a wide variety of topics in quantum computing and quantum information theory. What are you going to do? You are expected to: carry out original
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developing new explanation methods. This will involve using tools from mathematical machine learning theory to prove mathematical guarantees about the performance of such new explanation methods, as
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our PhD students to become experts in and define a research agenda around a topic of their choosing. The new PhD student will be part of the Business-Society department. Our department is unique in its
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to have knowledge of discrete-event systems, and knowledge of or interest in learning about formal methods, in particular, the theory of Supervisory Controller Synthesis. PhD 4: AI-driven legacy system
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coursework provides a strong foundation in both theory and quantitative methods, preparing you to design and carry out empirical studies. In addition, you will be actively involved in the department’s research
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machine learning approaches to quantitatively analyze experimental data and predict emergent multicellular behaviors under varying mechanical and chemical environments. For more information about our lab
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theories and models. This project aims to develop new insights into how bedrock incision processes interact with geological and climatic factors (i.e. spatially variable uplift, shield building, mega
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of the literature in this area and the ability to develop a solid research proposal drawing from theory in psychology and or the social sciences. These references may assist as starter references: Whitty, M. T. (2025