116 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Ghent University
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. For more information about this vacancy, please contact prof. Petra Van Damme (petra.vandamme@UGent.be , +32 (0)9/264 51 29). Where to apply Website https://academicpositions.com/ad/ghent-university/2026
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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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on various aspects of (micro)palaeontology, which will constitute a rich and exciting working environment for the successful candidate. https://www.ugent.be/we/geologie/en/research/organization/palaeontology
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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
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regarding the online application process? Please read the FAQ or contact us via selecties@ugent.be . Where to apply Website https://academicpositions.com/ad/ghent-university/2026/scientific-researcher-29
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question regarding the online application process? Please read the FAQ or contact us via selecties@ugent.be . Where to apply Website https://academicpositions.com/ad/ghent-university/2026/assistant
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the FAQ or contact us via selecties@ugent.be . Where to apply Website https://academicpositions.com/ad/ghent-university/2026/postdoctoral-researcher-… Requirements Research FieldArchitectureYears
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with both experimental research and simulation software. You possess strong technical knowledge, expertise, and hands-on experience in the field of electric machines. Additional knowledge of power
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technical knowledge, expertise, and hands-on experience in the field of power electronics. Additional knowledge of electric motor design and the control of electric machines is considered an asset. You have
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researchers from IDLab-AIRO (robotic experts) and imec. Your main tasks include: Reviewing literature on decentralized control frameworks in the domain and machine learning algorithms compatible with