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strong foundation in either data science, electronics, or systems engineering—with a deep curiosity to learn the others. Professional qualifications: Educational background: You hold an MSc in
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of this PhD is to develop physics-informed neural operator frameworks that embed governing equations and invariants of fluid mechanics directly into learning architectures, enabling real-time, generalizable
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. This position offers an exciting opportunity to work in a dynamic, innovative research environment. Labor Contract: https://ucnet.universityofcalifornia.edu/labor/bargaining-units/px/index.html Lab: https
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external research groups, and a planned experimental program in biophotonics. The position is based at Schloss Kränzlin near Neuruppin in Brandenburg — a quiet, focused environment for deep scientific work
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subsea digital twin of deep-water mooring lines for floating offshore wind turbines. The digital twin will be integrated with machine learning algorithms for detection of primary entanglement due
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. The researcher will develop novel research that applies advanced data science, machine learning and deep learning to various different data modalities. An ambition of this team is to implement predictive modelling
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that could redefine how we treat osteoarthritis? We are looking for a motivated PhD candidate for a cutting-edge project at Radboudumc that aims to unravel and therapeutically target dysregulated energy
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, from linear models to deep learning, depending on what best fits a given problem. The most successful researchers will be driven by a curiosity for how their contributions fit into the larger picture of
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learning, deep learning, and large language models, as well as advanced AI courses aligned with their professional interests. Applicants must submit a cover letter, a CV, and a statement summarizing teaching
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mutations, etc.), analysis and integration of mass-spectrometry proteomics datasets, and artificial intelligence/machine learning (AI/ML) and systems-biology-focused efforts (i.e. large genomics and