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PhD Position - Operando X-ray Characterization of Catalytic Interfaces for Chemical Hydrogen Storage
decomposition. The scientific objective is to resolve active-site formation, interface processes, reaction intermediates, structural evolution, deactivation, and regeneration, and to translate this understanding
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the development of AI-powered smart care solutions. The position is at the Department of Computer Science, Electrical and Space Engineering, Division of Computer Science, at Luleå University of Technology (LTU
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in vitro and in vivo studies will be performed to evaluate the safety and efficacy of the developed (nano)hormone-chemotherapeutics. A key stage of the project will involve the development of a
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joint projects, academic networks and participation in scientific conferences; contribute, as required, to teaching, curriculum development and the supervision of master’s and doctoral theses; provide
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joint projects, academic networks and participation in scientific conferences; contribute, as required, to teaching, curriculum development and the supervision of master’s and doctoral theses; provide
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projects, academic networks and participation in scientific conferences; contribute, as required, to teaching, curriculum development and the supervision of master’s and doctoral theses; provide scientific
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joint projects, academic networks and participation in scientific conferences; contribute, as required, to teaching, curriculum development and the supervision of master’s and doctoral theses; provide
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projects, academic networks and participation in scientific conferences; contribute, as required, to teaching, curriculum development and the supervision of master’s and doctoral theses; provide scientific
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Your position You will work on the development of a nanopore-based platform for single-molecule analysis of nanoclusters. Your research will include: • Establishing nanopore assays for detecting and
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predictions of river flow direction and connectivity. You will lead the development of scalable and reproducible data and machine-learning pipelines, upgrade the GRIT global hydrography, and design and evaluate