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TASKS The Marchal lab (IDLab/IMEC Ghent University, https://idlab.ugent.be/people/802000961346 ) has an open PhD position within the Marie Sklodowska-Curie Doctoral Networks (MSCA-DN) project iSTRIDE
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particular the research lines of Professors Seppe vanden Broucke (e.g., applications of deep learning, graph learning, geospatial analytics, process mining), Frederik Gailly (e.g., ontologies, knowledge graphs
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and/or machine learning Interest in biology or molecular biology, microbial ecology Proficiency in programming languages such as Python, R and/or C++ as well as Linux systems. Fluency in spoken and
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)palaeontology, which will constitute a rich and exciting working environment for the successful candidate. https://www.ugent.be/we/geologie/en/research/organization/palaeontology-and-palaeo-environments https
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on experimental data which you acquire. You publish the research results in scientific journals and present at international conferences You contribute to the supervision of master and PhD students At least 70% of
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machine learning. This encompasses application domains such as industrial inspection, (ultra) high-definition video enhancement, smart multi-camera networks, computer vision, sensor fusion, and (medical
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of statistics, computer science and/or machine learning Interest in biology or molecular biology, microbial ecology Proficiency in programming languages such as Python, R and/or C++ as well as Linux systems
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of thermal energy and (hybrid) machine learning in which physics-based models are combined with data-driven techniques. Thermal cycles make it possible to meet the demand for heating, cooling, and electricity
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their results in the context of the clients. Analyses will be conducted with several software packages for statistical data analysis (possibly including R, SAS, Python, …). The new colleague may acquire new
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perspective, including (but not limited to): machine learning and statistical learning computer vision and sensor-based data analysis natural language processing and large language models hybrid, interpretable