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these fields is not required, what we are looking for is a strong motivation to learn, adapt, and apply these technologies to advance microbiome research. Profile We are looking for a driven and creative PhD
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relationships. You are motivated to acquire new skills and work in a multidisciplinary team. You have practical experience with experimental work and data analysis. You act with attention to quality, integrity
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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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for focal epilepsy with ultrasound neurorecording, modulation, and deep reinforcement learning (DRL) closed-loop control. The technology will be developed through detailed computer simulations and preclinical
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is focused on enabling applications through a fundamental understanding of material formation processes and properties. KU Leuven (University of Leuven) has been a center of learning for nearly six
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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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that he/she can check approve your file . You will have to upload some documents Proof of enrolment as a PhD student at your home University A signed Learning Agreement. Please chose the correct template
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your knowledge and skills on state-of-the-art in machine learning, (probabilistic) modelling, system identification and numerical optimization. How to apply Send your CV containing one or more references
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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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interest to acquire those in exercise physiology, metabolic & inflammatory regulation, molecular biology and biochemistry. Experience with basic molecular biology techniques, such as protein/mRNA extraction