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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
replace or supplement traditional planning approaches, which struggles to manage the uncertainty and variability that are inherent in complex engineer-to-order shipbuilding. Realizing the full potential
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into valuable aromatics and specialty chemicals. In this project, you will design and study catalytic processes that upgrade complex phenolic mixtures into targeted products using advanced bifunctional catalysts
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discoveries of today. At locations in Berlin-Buch, Berlin-Mitte, Heidelberg and Mannheim, our researchers harness interdisciplinary collaboration to decipher the complexities of disease at the systems level
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to explain the observed matter-antimatter asymmetry in the universe. The SM is therefore likely a low-energy limit of a more complex theory, and the Higgs field is one of the most useful tools for determining
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vehicles and achieving net-zero targets, but they degrade over time, reducing performance and safety. A key issue is gas generation, which causes internal pressure build-up and can lead to cell failure, but
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higher degree of complexity in materials, geometries, and length scales. As a result, the design of such systems has become quite a challenge. This becomes even more challenging when considering
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candidate possesses: A Master’s degree in Environmental Economics, Psychology, Complex Systems, Engineering & Policy Analysis, or a related field; Experience with data analysis and statistical methods; A
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-centric AI and explainable decision-making? Are you intrigued by the role of human expertise in complex optimization? This PhD position focuses on bringing humans into the loop of optimization processes
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The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences | Poland | about 2 months ago
CtBP-mediated transcriptional repression and reorganizes transcriptional corepressor complexes. By integrating molecular biology, cell biology, quantitative microscopy, biochemistry, proteomics, and
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the development and application of nonlinear dynamical systems methods for complex physical problems known only from data. The objective is to provide efficient, theoretically sound, fast, and directly