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models combining machine learning, and physics-of-failure (PoF) approaches using in-situ data • You work on projects independently • You will present your work at international conferences and
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. You have a good knowledge of Python and machine learning. You have an excellent knowledge of English. Your research qualities are in line with the faculty and university research policies . You act with
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regulatory network reconstruction and wide range of machine learning approaches The host labs will provide financial support for the whole length of the PhD. The applicant will be expected to seek independent
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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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are looking for a m/f/x Doctoral fellow YOUR JOB You conduct doctoral research in the area of Augmenting Learning Environments Using Generative AI and Neuroadaptive Systems, with the aim to obtain a PhD after
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modeling into modern causal inference by combining its strengths with innovations in debiased machine learning, as well as to improve both the statistical efficiency and robustness of debiased machine
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interdisciplinary research team, focusing on human-robot interaction, unconventional robotics, cognitive systems and machine learning. You will have access to the full facilities of IDLab, including high-performance
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techniques) at UGent combined with machine learning, deep learning and data fusion modelling to enable development of novel decision support systems for variable rate fertilization and manure application. He
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and near infrared, mid infrared and advanced machine learning and artificial intelligent modelling to enable accurate monitoring of nitrogen mineralization rate to enable understanding and improving
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Job description PhD position in computational neuroscience - Deep reinforcement learning closed-loop control for the treatment of epilepsy As part of the highly prestigious ERC Starting Grant