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. Finally, the research will develop efficient algorithms and test them on realistic networks and using real data from energy and public transport operators. The Doctoral student is also expected
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or to: TU Dresden, Chair of Algorithmic and Structural Graph Theory, Prof. Daniel Neuen, Helmholtzstr. 10, 01069 Dresden, Germany. Please submit copies only, as your application will not be returned to you
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the 01.02.2026 at the following conditions (PhD position): 50% = 19,92 hours Pay grade 13 TV-L limited 30.11.2028 Your tasks: Develop AI algorithms for real-time fault detection, fault classification
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to optimise built-environment thermodynamics and occupant comfort by creating predictive AI tools for spatiotemporal heat transfer. Machine learning algorithms will identify energy inefficiencies and propose
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No: 101227148) and coordinated by the University of Bergen, Norway. Supervisors: Prof. Martin Reincke , Prof. Nicole Reisch Location: Ludwig Maximilians University Hospital Munich, Germany Duration: 3 years
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will be based in Odense, under the primary supervision of Prof. Ricardo J. G. B. Campello , but they will be expected to also work closely with other PhD students, postdocs, and collaborators both from
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high dynamic range (HDR) imaging is redefining the way smartphone cameras and displays capture the world. Despite HDR becoming the new standard, many classic image-processing algorithms and generative
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of elements) of the model.; 3) develop an optimization algorithm based on genetic algorithms and metamodels and 4) design functionally graded OC scaffolds using different biomaterials. The doctoral candidate
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Ingolstadt. The salary is prescribed by the framework of the collective agreement (TV-L), Level 13 (75%). The research group Reliable Machine Learning (headed by Prof. Felix Voigtlaender) is part of
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participants of the Netherlands Twin Register, integrating genetic and psychological data where relevant. Beyond algorithm development, you will also address methodological challenges such as data quality, bias