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ultracold gases or condensed matter systems. Experience with numerical simulations is expected, along with a high level of motivation and a genuine interest in fundamental research. About You To be suitable
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, optimization) or AI.- Someone who enjoys working in a team, takes initiative, and isn’t afraid to think outside the box.- Someone with excellent grades from BSc and MSc studies, and not afraid of experimental
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the development of system software. Key questions include how LLMs can support programmers in writing complex logical code, generating high-quality tests, and optimizing performance. Moreover, when integrated with
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Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
with gene expression and cell surface remodelling. Systems Biology of Bacterial Defence – Integrating Multi-Omics to Model Microbial Survival: Outside of optimal laboratory conditions, bacterial cells
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, Mechanical, Electrical or a related field) Solid background in the energy domain, ideally with experience in various energy forms (electrical, thermal, etc.) Interest and skills in numerical modelling Fluency
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, and more efficient operations. After all, the greenest energy is the one that’s not spent – and this project aims to unlock just that by refining the way we design and optimize airfoils. The focus
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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from 150 nations, located on the border where Switzerland, Germany, and France meet. A large number of institutions for biomedical research, with numerous possibilities for training, networking, and
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Department of Mechanical Engineering and the AI research group at the Vrije Universiteit Brussel (VUB) are looking for a PhD candidate to contribute to research on the optimization of a hybrid, laser-based
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for remote applications: A crucial aspect of this project will be the optimization and deployment of developed signal processing and machine learning algorithms onto resource-constrained edge devices