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Field
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. As part of this PhD, the candidate will: Conduct an integrative review of established competency models Create assessment tools (which may include use of AI tools) to measure CLMA proficiency
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on addressing the complexity of the device-software-application-data design space, enabling systematic and efficient exploration using modeling and simulation tools.## Key Responsibilities- Identify and
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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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transitions, flow dynamics, stratification) inside thermal storages containing PCMs? How can we describe via validated multi-physics simulation models; heat transfer, flow behavior, and phase changes? Your task
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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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will be trained in a variety of powerful, modern analytical techniques including chemical proteomics and metabolomics. They will have access to advanced synthesis facilities, as well as biological models
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such as model-based optimal control and nonlinear reset control. The goal is to push beyond commercial standards, achieving unprecedented sensitivity by overcoming mechanical and interferometric noise
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home office allowance of €2 per day. Reimbursement for sustainable commuting: walking, cycling, and public transportation. A monthly internet fee of €25. An Options Model in which you exchange benefits
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following: soft-robotics, compliant mechanisms, mechanical metamaterials, smart materials or related topics. Capability in computer drawing, modelling and simulating. Proficient in English reading and writing
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operational performance. Based on feedwater composition (salinity, monovalent/divalent ion ratios, and valuable elements), you will model and design ED configurations that produce tailored concentrate streams