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are looking for talented people to join us. Your responsibilities include: MI Project IE2501 “Safe Hydrogen Networks: ML-Supported Safety Analysis and Optimized Sensor Placement” Research in the field of safety
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qualification (usually PhD). Tasks: The aim of the project is to design, model, fabricate and test a wireless micro-sensor which uses magnetic fields for sensing in biological soft tissues. For further
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their glial niche. Genetically encoded, fluorescent metabolite sensors will be used to study the underlying metabolite dynamics. The work will also incorporate various molecular biology techniques, as
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in mechanobiology and translational cardiovascular research would be advantageous WE OFFER: Dynamic and collaborative research team of experienced and early-career scientists Embedded in a network of
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
(MSCA) doctoral network led by Prof. Cecilia Persson, Uppsala Universitet. Print4 Life – Advanced Research Training for Additive Manufacturing of the Biomaterials and Tissues of the Future https
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on mechanistic study of high cor
network led by Prof. Cecilia Persson, Uppsala Universitet. Print4Life – Advanced Research Training for Additive Manufacturing of the Biomaterials and Tissues of the Future https://cordis.europa.eu/project
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research environment and part of various research networks. Our research focuses on investigating single cell and population dynamics during innate immune responses. The successful applicant will join an
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on mechanistic study of biodegra
Marie Skłodowska-Curie (MSCA) doctoral network led by Prof. Cecilia Persson, Uppsala University. Print4Life – Advanced Research Training for Additive Manufacturing of the Biomaterials and Tissues
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specifically, the computational team will build on our previous work (PMID: 38951512) to establish and train deep neuronal network models on large existing dataset with multi-omic data. Subsequently
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provide a dynamic environment which empowers excellence with state-of-the-art technologies, cutting edge infrastructure, and a global scientific network. Contribute your knowledge, vision, and dedication