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encapsulation strategies to improve stability and controlled release of bioactive compounds. The project will also develop prototypes for human food, pet nutrition and cosmetic applications to validate
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connected with industry partner, Avoncourt Packaging. The project aims to improve the collection and transformation of fine PET plastic dust into a reusable form for recycling, with a focus on energy
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, including glass and flexible PET sheets. Design and validate complex photochromic ink configurations to achieve multiple colors and gradients. Evaluate the morphological and mechanical properties
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Research Scholarship of Post-Doctoral Research for the scientific area of Chemistry - IST/2025/BL103
for in vivo recognition of FAP. The biodistribution of the radiolabeled miniproteins will be evaluated in animal models. PET/SPECT imaging will be performed to assess their pharmacokinetics and to support
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the collection and transformation of fine PET plastic dust into a reusable form for recycling, with a focus on energy efficiency. The role involves hands-on laboratory work to design and test a small-scale process
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any of the following areas of expertise or experience are strongly encouraged to apply: Prior experience with Monte Carlo radiation transport simulations, preferably GATE/Geant4 for PET and/or SPECT
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staff position within a Research Infrastructure? No Offer Description Turku PET Centre is looking for a Postdoctoral Researcher for a fixed term position, starting 1 February 2026, ending 31 March 2028
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vivarium, a cell culture room, and state-of-the-art flow cytometry, microscopy, and next-generation sequencing equipment. Furthermore, our cutting-edge imaging facilities (including PET, MR, IVIS, and CT
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Infrastructure? No Offer Description The Project is funded by NCN under the SONATA BIS-13 program. Project Title “μPPET: studying the Cosmic Rays Muon Puzzle by probing muons with J-PETs” Where to apply E-mail
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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models