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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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, testing, and demonstration of novel CCUS technologies Process simulation, cost, life cycle, and social assessment of CCUS value chains Reactor design, optimization, and sizing using phenomenological and/or
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testing, and advanced process simulation, with the objective of optimizing grinding performance and enhancing resource recovery. The ideal candidate will have a strong background in mineral processing
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of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict ore quality and optimize operational decisions. 2. Key Responsibilities
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frameworks, applying existing frameworks, and implementing novel methodology in shared code repositories. You will also assist in instructing and guiding the research of MSc and PhD students. Qualifications As
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. This position offers an exciting opportunity to work at the intersection of HPC and AI, addressing critical communication bottlenecks and optimizing network interconnects for large-scale distributed systems
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help! We have several fully-funded open PhD and Post-Doc positions (m/f/d, E13 TV-L) in our group - which just moved from the Max Planck Institute in Erlangen to the University of Tübingen, one
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optimized, you will apply the technique to solve open questions on the structural transformations occurring in batteries during cycling. The preferred starting date is 1 December 2025. Profile You hold a PhD
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of water intended for agricultural use. The selected candidate will contribute to the development and optimization of desalination processes (membrane-RO), the analysis of treated water quality (especially
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is 7/1/24. Qualifications Completed PhD or a foreign equivalent. The current project seeks to revolutionize the entire process from data to prediction with a paramount focus on reproducibility and