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PhD research will focus on characterizing and optimizing architectured fabrics and textiles using 3D micro tomography as a main tool to investigate tribological and thermal properties of different
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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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, 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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functionalized lignin as a precursor for carbonaceous structures – Produce optimized ink formulations for laser-induced graphitization processes using functionalized lignin oligomers – Characterize the materials
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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
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concept is the use of plasma technology. Your tasks This PhD position will contribute to the SNSF-funded Ambizione project Plasma4Water . Your main task will be the design, fabrication and optimization
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from cell-, thrombus-, and organ-level perspectives? While being part of a prestigious MSCA doctoral network working on revolutionizing personalized medicine through cutting-edge in silico, in vitro, and
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applications in forecasting, system optimization, flexibility management, and resilience analysis. The work will be carried out in close collaboration with our interdisciplinary teams at both Empa and EPFL, as
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-duration energy storage. The approach is to use hierarchical structures, i.e. complex material layers that can be optimized to specific battery chemistries and flow phenomena from the microscale up
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-duration energy storage. The approach is to use hierarchical structures, i.e. complex material layers that can be optimized to specific battery chemistries and flow phenomena from the microscale up