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Field
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11 Dec 2025 Job Information Organisation/Company Universität Siegen Research Field Computer science » Informatics Researcher Profile First Stage Researcher (R1) Country Germany Application Deadline
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Mathematics (Inverse Problems), Computer Science (Machine Learning, Computer Vision, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of
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, their achievements and productivity to the success of the whole institution. The Faculty of Computer Science, Institute of Theoretical Computer Science, the Chair of Algorithms offers a position as Research Associate
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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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Mathematics (Inverse Problems), Computer Science (Machine learning, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of the NXTGen High-tech
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supervisor: Dr. B Adams [XYZT], Co-supervisors/mentors: Prof. H. Sallouha [KUL], and Dr. R. Martinez [KUL] Required profile: Telecommunications, Electrical Engineering, computer science Desirable skills
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the computational biology and bioinformatics field. Developing specialized methods for automatic or semi-automatic, possibly visually aided evaluation and model selection of such algorithms. Developing tailored
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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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“Stability and Solvability in Deep Learning”. This project focuses on mathematically analyzing machine learning algorithms with a particular focus on questions of stability, computability, and robustness
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, and model validity. This project is a collaboration between the Department of Biological Psychology (Prof. dr. Meike Bartels & dr. Dirk Pelt) and the Department of Computer Science, AI research