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comparable degree at the same academic level). Nice to have (role dependent): Specialization in agricultural/field/industrial robotics, mechatronics, embedded systems, or wireless communication (PhD#1 and #2
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rule ) immediately before the recruitment date. The research Environment As a PhD Student, you will be embedded in a strong research community that is internationally recognized for excellence in
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will follow the PhD study program at the Faculty of Science. This position is embedded in the project “PARAMLP: Parameterized Algorithms and Polyhedra” funded by the ERC . The ERC is the premier European
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vocational education. While the PhD fellow is expected to contribute to this overarching agenda, the position also allows and requires the development of an independent subproject. This means that the PhD
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diffusion techniques to design materials with targeted optical properties, scaling to large systems through efficient representations and GPU parallelization. We will also create multi-fidelity predictive
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neurotechnology. Project Overview This PhD project is embedded in a multidisciplinary initiative that aims to develop a wearable neuromorphic system for brain-signal interpretation and sensor-based feedback
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on conventional computing platforms such as GPUs, CPUs and TPUs. As language models become essential tools in society, there is a critical need to optimize their inference for edge and embedded systems