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in AI and Optimization 80 % Start of employment 1st of March 2026 or by agreement, temporary The Department of Mathematical Modeling and Machine Learning (DM3L) at University of Zurich is seeking
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-to-end virtual supply chains. This project also aims to optimize other thermal processes using digital twins, such as thermally-steered drug delivery processes for applications in oncology. PhD position
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, based on measured air temperature and humidity data in cold chains by commercial sensors, and deploy them in end-to-end virtual supply chains. This project also aims to optimize other thermal processes
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economic impact of optimized cooling solutions and refrigerated supply chain solutions. Your tasks The priorities of the tasks will be flexibly decided depending on the concrete opportunities at hand after
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) distributional generalization, transfer learning, causality Multi-objective settings and alignment, RL theory Statistical learning theory, optimization (e.g., implicit bias) Robustness (broadly defined), privacy
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, investigations and optimization of hydrogen production via methane pyrolysis for decarbonization of industrial high-temperature processes with potential for negative carbon emissions. Your tasks Setup
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on microfluidic and physical principles, fabricate & optimize using state-of-the-art microfabrication techniques and characterize chip performance (fluidics, mechanics, and reproducibility). Method development
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, Human-Robot Interaction, Imaging Technology, Machine Learning, Medical Informatics, Medical Robotics, Natural Language Processing, Neuroinformatics, Optimization, Perceptual Inference, Probabilistic
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learning, optimization, or intelligent systems. Prior experience with embedded platforms, signal processing, or model compression is a plus. We value creativity, curiosity, and the ability to connect ideas
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knowledge and understanding in pyrolysis processes we are looking for a PhD student for scientific analysis, investigations and optimization of hydrogen production via methane pyrolysis for decarbonization