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Max Planck Institute for Chemical Energy Conversion, Mülheim an der Ruhr | M lheim an der Ruhr, Nordrhein Westfalen | Germany | 23 days ago
methodologies. The appointed researcher will be performing electrochemical reactions and tune reaction conditions to optimize for products of high (industrial) relevance. The student will also be involved in
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the optimization and validation of new assays in compliance with regulatory standards to make them clinically available (e.g., IVDR, ISO 15189, ISO 17020) Contribute to the certification and implementation
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system for H2 production. This thesis will focus on optimization of innovative coating methods to fabricate and characterize MEAs and evaluate their electrochemical performance. What you will do Experiment
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An international, committed, and collegial working environment Excellent scientific equipment and the latest technology Qualified supervision by academic colleagues Optimal conditions for balancing work and private
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optimizations (e.g., Access Traffic Steering, Switching, and Splitting (ATSSS)) for contributing to relevant standardization bodies Implementing prototypes involving congestion control and multipath over QUIC
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services for the evaluation and optimization of climate-neutral industrial processes and high-temperature storage. Storage technologies are crucial for the energy transition. We use simulations and
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transmission schemes, protocols and cross-layer optimizations for contributing to relevant standardization bodies Implement prototypes involving machine learning techniques to optimize for latency, reliability
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. Using a techno-economic optimization approach based on the Python-based open-source framework ETHOS.FINE, regionalized hydrogen cost potentials are derived to support decision making in industry, policy
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) (subject to personal qualification, employees are remunerated according to salary group E 13 TV-L) starting July 1, 2025. Research areas: Cross-domain/cross-platform transfer learning, ML-optimized code
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) (subject to personal qualification, employees are remunerated according to salary group E 13 TV-L) starting July 1, 2025. Research areas: Cross-domain/cross-platform transfer learning, ML-optimized code