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Field
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field; Affinity with formal methods, including an understanding of basic of automata theory, formal languages, algorithms, and computability --- i.e., foundational computer science theory. Candidates with
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allow you to explore the fundament physical limits of the technique and to create new image reconstruction algorithms. This project offers the opportunity to produce new techniques in imaging physics
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
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. The project will focus on the development a set of robotic prototypes capable of both climbing and manipulating large-scale space assets using a combination of novel gripper designs and locomotion algorithms
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the utility and the robustness of different explanation strategies. A large focus of this project will be on leveraging novel and interpretable approaches in applied domains such as algorithmic fairness and
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involves the use of quantum chemistry, machine learning, and genetic algorithms to search for new homogeneous chemical catalysts. Who are we looking for? We are looking for candidates within the field
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, programming and algorithm development, automation and online analytics. This project would be ideal for an ambitious and innovative researcher who enjoys working in a diverse and interdisciplinary team and is
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we