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project’s principal investigator, Associate Professor Lars Rohwedder, an internationally recognized expert in the areas of approximation algorithms and parameterized algorithms, see https://larsrohwedder.com
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Your tasks: Developing optimization algorithms for massively parallel hardware architectures such as AI
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on the complementary expertise and recognized excellence of its 22 research teams to contribute to the development of the fundamental aspects of computer science (models, languages, methods, algorithms) and to foster
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algorithms into electron impact ion sources as well as tackle changes over time in ISOL systems, to ensure an optimal tuning at any point in time during operation. Where to apply Website https://www.sckcen.be
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simulation of scenarios with different materials and geometries. - Support the development and implementation of signal and image processing algorithms, including fast inversion techniques, FFT, and nonlinear
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oriented, regionally anchored top university as it focuses on the grand challenges of the 21st century. It develops innovative solutions for the world's most pressing issues. In research and academic
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simulations and thermal comfort analyses by developing fast parametric algorithms and data-driven surrogate modelling approaches capable of predicting dynamic outdoor thermal comfort with high accuracy
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electrochemical phenomena. · Propose non-invasive diagnostic methods based on this digital twin. · Develop algorithms to speed up or standardize the determination of the parameters of this digital
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, development, and training of machine learning and deep learning algorithms. Creation of accurate, robust, and energy-efficient models. Development of systems capable of predicting and making decisions in real
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propagation models that incorporate the effects of fire effluents, validated through controlled experimentation. You will develop tomographic inversion methods and anomaly-detection algorithms capable