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of debiased machine learning methods. This PhD project will primarily focus on the foundations of an assumption-lean modeling paradigm, with a strong focus on the analysis of repeated measures outcomes, in
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, these methods are more and more combined with machine learning techniques. BIONAMIX is a team embedded in the department of data analysis and mathematical modelling in the Faculty of Bioscience engineering. We
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, Agriculture Engineering (not agronomy), or Biosystems Engineering Basic knowledge in sensing technologies and measurement systems. Basic knowledge in machine learning, deep learning and/or data fusion and
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and measurement systems. Basic knowledge in machine learning, deep learning and/or data fusion and modelling tools, and eager to learn about more advanced modelling techniques. User of engineering
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, bioinformatics and machine learning, as well as high-throughput biology in the framework of gene regulatory networks. Our final goal is to use this knowledge in the development of novel preventive or therapeutic
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analyses, survival analysis, machine learning). Job profile You hold a master's degree (preferably) in medicine, biotechnology, bioengineering, biomedical sciences, pharmacy or equivalent. Diploma
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Research staff Job description Vacancy: PhD position Deep Learning on Time series Data for Health Care ABOUT GHENT UNIVERSITY Ghent University is a world of its own. Employing more than 15.000 people, it is
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necessary at the start of the PhD. (4) You have a problem-solving, analytical mind, dedicated to overcoming technical challenges. (5) You have an open attitude towards learning, and are driven, hard-working
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not necessary at the start of the PhD. (4) You have a problem-solving, analytical mind, dedicated to overcoming technical challenges. (5) You have an open attitude towards learning, and are driven, hard
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task. You develop methods for aligning the ontologies to check for semantic, syntactic and structural heterogeneity. You will investigate the use of machine learning algorithms for automatic ontology