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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with machine learning methods with the support of
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on developing a fundamental understanding and numerical models for multiphase flows, which are crucial for various industrial processes. The successful candidate will develop advanced physics-based methods in
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treatment method. We conduct research across a broad range of areas, including trauma, degenerative disease, pediatric orthopedics, and hand surgery. Depending on the research question, we employ a wide
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theoretical analysis, implementation of methods in computer codes, use of state-of-the-art high-performance computers in Sweden and in Europe, application of machine-learning and AI techniques, and
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methods in breast cancer diagnostics, with a particular focus on cancer screening and artificial intelligence. Located at the Skane University Hospital (SUS) Malmö, Diagnostic Radiology and LUCI are both
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methods in fluid dynamics and heat transfer to study multiphase flow phenomena. The goal is to integrate theoretical and experimental fluid dynamics with modern computational tools to analyze and predict
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to improve targeting of ON-based drugs to B cells using protein-based targeting methods coupled with studies related to endosomal escape properties of the ON after internalization. We will employ the novel
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will contribute to the development and evaluation of methods for bioprinting hydrogels (also referred to as bioinks) that support the development of better 3D in vitro models with such tissue-specific
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networks (CNNs), which identify local correlations in the images. However, in this project, the aim is to go beyond standard CNN-based methods by developing new approaches based on transformers, and implicit
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the DC will use pore-scale direct numerical simulations (based on the lattice-Boltzmann method) to enable the precise quantification of mass transport within electrode microstructures, reconstructed via X