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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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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
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preservation from digital twins, so extra shelf life, to economical advantages. Integrate these digital twins into other platforms, such as mobile applications. Extend the digital twin work to optimize thermally
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-agents for perception and communication. Candidates ideally have a background in computer science, electrical engineering, or related fields, and a strong interest in machine learning, optimization
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how perishable biological products, such as vaccines, react inside cold chain unit operations and to pinpoint why some products decay faster. For that purpose, we develop digital twins of the cargo
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, aligning AI systems with complex human values, and building self-improving agents capable of autonomous learning. Our work combines cutting-edge experimentation – spanning RL, meta-learning, and robust
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Doctoral Network funded by Marie Skłodowska-Curie Actions (MSCA-DN) that aims to revolutionize Bio-fibre composite landscape by designing high-performance, fully renewable, and recyclable wood and plant
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be used to address the following questions: What are the mechanisms of embolization of the lung? Can we predict where thrombi end up? What are the optimal drug infusion protocols for efficiently
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possibilities and our pronounced vocational training culture. If you wish to optimally combine work and family life or other personal interests, we are able to support you with our modern employment conditions