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computational and experimental techniques in a high-tech industrial-academic setting. Develop constitutive material models tailored to recycled aluminum sheet forming, and implement them within commercial FE
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effective for designing and optimizing applications for reconfigurable/spatial computing architectures (HW/SW co-design)- Extend or build simulation or modeling frameworks to support systematic exploration
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Vacancies EngD Position: Simulation-Guided Downgauging and Process Optimization of Recycled-Content Aluminum Trays (EcoTray) Key takeaways The focus lies on advancing the digital and experimental
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to this challenge is to leverage assets such as grid-level battery storage, and electrolyzers to have more flexibility when making trading decisions. The challenge then is how to optimally leverage such an asset
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models for optimized selection of treatment before, and follow-up after EVAR. You will implement and advance multimodal deep learning models combining CT imaging and clinical data, trained on the unique
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profitability. Examples include optimizing production speeds to balance output, equipment deterioration, and energy consumption in manufacturing, or designing dynamic pricing and allocation policies in rental
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flexibility. To fully unlock this potential, we need advanced tools that digitally replicate these networks and support optimized design and data-driven control strategies. As our PhD candidate, you will
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business analyst are: Understanding the wishes and requirements of the business by clarifying the customer questions and, together with architects and developers, defining the most optimally suitable
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a driving force behind effective Agile working methods. You support teams and Product Owners in delivering value and optimizing processes. In addition, you will contribute to the broader Scrum Master
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Today, companies across a wide