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Field
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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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provides a unique opportunity to work at the intersection of AI and experimental science, combining fundamental algorithmic development with real-world applications in scientific imaging. Due to limitations
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will develop autonomous on-board guidance algorithms for space missions using open-source numerical solvers for convex optimisation developed at the University of Oxford. The focus will be on designing
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intersection of AI and experimental science, combining fundamental algorithmic development with real-world applications in scientific imaging. Due to limitations in electron dose and scan stability, microscopy
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needs. By bridging human-centric innovation, generative algorithms, and sustainability metrics, this project seeks to redefine how novel products and systems are conceived, developed, and evaluated. You
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Description We are looking for a PhD-candidate interested in topics that lie on the border of optimization by the use of heuristic algorithms and (Explainable) Artificial Intelligence ((X)AI). Specifically, in
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algorithms) Proficient in English. For information please check the Graduate Schools Admission Requirements. Familiarity or interested in using machine learning is also desiered. TU Delft (Delft University
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: Fulltime Are you interested in working in an ambitious team that combines genomics and tumor evolution to better understand pediatric cancers? Do you have a passion for understanding why some cancers resist
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Are you interested in working in an ambitious team that combines genomics and tumor evolution to better understand pediatric cancers? Do you have a passion for understanding why some cancers resist
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase