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consumption while guaranteeing optimal power production. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop graph-based
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attacks Develop and implement ML algorithms to identify vulnerabilities and predict potential threats in supply chain systems Prepare project deliverables and disseminate results through high-quality
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into their workflows. You will benchmark the supports, MEMS devices and developed codes on known multiphased reference samples. The TEM will be done at EMAT (University of Antwerp) under guidance of Prof. Dr. Joke
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analysis, data modeling, and algorithm development. Experience with environmental analysis or microplastic research is a plus but not required. Strong analytical and problem-solving skills, ability
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
Job description We are seeking two highly motivated postdoctoral researchers to join our research team based in the Van de Peer lab, under the supervision of Prof. Dr. Zhen Li, Assistant Professor
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and grippers offer improved safety and adaptability but introduce new challenges in design and control. Their development is still largely bio-inspired and trial-and-error based. Integrating flight and
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. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop machine learning surrogates of wind energy systems. As newer
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. Hiep Luong (Dept. of Telecommunications and Information Systems, FEA); Prof. Dr. Thomas Hermans (Dept. of Geology, FW) Project summary In this research, we develop and optimize geophysical survey
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, storage and demand. YOUR TASKS You will develop mathematical models and metaheuristic algorithms for complex optimization problems in the context described above, see e.g., https://arxiv.org/abs/2503.01325
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collaboration with other PhD candidates and researchers with medical and engineering background, perform innovative research on the topic of surgical video analysis, with the goal of developing deep machine