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to real-world problems. You will join the CHOIR research group, known for its strong care provider network and impactful healthcare operations research, with the PhD topic shaped collaboratively with your
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. Your work will focus on design-space exploration and optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g., term rewriting), to algorithmic
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, business school scientists, system modeling and optimization researchers, computer scientists, legal experts and social scientists working on energy topics. Description of the PhD project The project
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optimization; Highly motivated to both perform foundational machine learning research and apply the developed methods in real applications; Creative, ‘making things work’ mentality, independent, and
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on performance bounds, radar design, and adaptivity. Job description The focus of this research project is on the optimal design of digital MIMO radar. In this context, we naturally think about the performance
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that balance energy supply and demand, improve electricity grid flexibility, and optimize renewable energy integration. These solutions contribute to climate change mitigation by reducing emissions and to
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the last-mile delivery sector. Concretely, the PhD candidate will perform research on understanding how self-learning optimization algorithms can facilitate efficient last-mile delivery operations
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department of Wageningen Livestock Research and is funded by a consortium of industrial partners. You will work here The research is embedded within the chair Animal Nutrition which is led by prof. Wouter
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-scale test results translate to full-scale performance. We are looking for a self-motivated and creative researcher with a strong background in multi-objective optimization, stochastic optimization, and
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Optimization and Machine Learning for Hydrogen Technologies The Natural Computing Group (NACO) at LIACS, Leiden University, is seeking a highly motivated researcher to join our cutting-edge project on AI tool