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the computational dosimetry framework for interventional procedures such that it can be implemented in hospitals. With current artificial intelligence (AI) technologies, and particularly machine learning (ML
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-type specific samples, state-of-the-art molecular biology techniques, multimodal data generation and integration, gene regulatory network reconstruction and wide range of machine learning approaches
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experience with time series data analysis and/or anomaly detection is a plus. I am proficient in Python and am familiar with data science and machine/deep learning toolkits. As a PhD researcher at KU Leuven, I
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knowledge and/or experience in several of the following topics: Optimisation algorithms Machine learning algorithms Swarm intelligence Algorithmics Parallel/Distributed computing Space systems engineering
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discipline The ideal candidate should have some knowledge and/or experience in several of the following topics: Optimisation algorithms Machine learning algorithms Algorithmics Smart buildings Internet
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, or any related engineering discipline The ideal candidate should have some knowledge and/or experience in several of the following topics: (Quantum) Optimisation algorithms (Quantum) Machine learning
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covariate adjustment of multivariate outcomes in clinical trials, causal machine learning, exponential random graph models for modeling mpox, demography and infectious disease epidemiology. You will
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have some knowledge and/or experience in several of the following topics (ordered by importance): Wireless Communication Technologies Distributed and Embedded Systems Machine Learning Data Analytics and
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Computational Biology PhD candidate to join our interdisciplinary team, focusing on how developing animal systems self-organize and acquire shapes. In our lab, we work with detailed registrations of embryos over
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of the professors of the Machine Learning group mentioned above, that is, Prof. Jesse Davis, Prof. Luc De Raedt, Prof. Tias Guns, Prof. Giuseppe Marra or Prof. Hendrik Blockeel. You will be part of a dynamic team