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compilation, optimization and error mitigation collaborate with theoretical computer scientists on developing noise-aware quantum programming paradigms Your Profile: Master in physics, computer science
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data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning, and artificial intelligence with
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aspects of biogenic dyes, from the identification of dye-producing bacteria and the characterization of their pigments, through the optimization of their production and application, to the comprehensive
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, experimentally grounded workflow for rapid microstructure-property optimization in steels. The PhD student will play a central role in this interdisciplinary initiative. They will: Develop and apply machine
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, microfabrication, materials optimization, and microwave control are highly preferred qualifications Please feel free to apply for the position even if you do not have all the required skills and knowledge. We may be
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for its strength in optimization, optimal control, dynamical systems, and applied mathematics in general. Mobile working A certified (Audit berufundfamilie) family-friendly work environment. Berlin is one
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- and ML-ready information to develop and implement an indirect inverse optimization framework to identify microstructures that exhibit desired macroscopic properties to publish and present research
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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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to female-biased disease along developmental trajectories. Your tasks and responsibilities Design and execute imaging-based high-throughput screening experiments Develop, optimize cellular assays and CRISPR
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Materials and Devices – Structure and Function of Materials (IMD-1) to establish a data-driven, experimentally grounded workflow for rapid microstructure-property optimization in steels. The PhD student will