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or heterogenous inorganic catalysts. The goal is to identify and optimize novel catalysts that can efficiently utilise solar energy by consecutively absorbing light with different wavelengths. Catalyst development
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Build and optimize workflows for analyzing biodiversity and entomological texts, focusing on functional traits, historical context, and geographic scope relevant to current environmental challenges
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Researchers: Ph.D. in Computer Science or Mathematics, ideally with a background in one or more of the following areas: Optimization, Game Theory, Machine Learning Applicants must demonstrate: • An excellent
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of Crystallography, RWTH Aachen University. Comprehensive training programs and individual opportunities for personal and professional development Comprehensive company health management Optimal conditions for
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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evaluate the strengths and limitations of eDNA versus acoustic monitoring (and other approaches), identifying optimal applications for each context. Best‑practice development: Co‑design guidelines and
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the international visibility of the research group. Contribution to methodological and technical innovation: You will develop and test novel technical approaches, optimize existing methods, and actively foster
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in the wild. The planned work involves optimizing IRL using agent-based simulations, applying IRL to empirical fish movement data to study reward functions in the context of adaptive strategies, and
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characterization and optimization Development and operation of continuous fermentation processes under strict anaerobic conditions Strategic contribution to platform development for metabolic engineering What you
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for compatibility with hydrogels and biological components. Optimize magnetothermal properties of nanoparticle formulations for heating in alternating magnetic fields. Create a magnetic heating setup to assess