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their scientific insights. All training is in English. The research The mission of our IMPRS is to study fundamental biological processes in plants and to create knowledge and material that can empower innovative
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30th November 2025 Languages English Norsk Bokmål English English PhD Candidate in Environmental Data Science (3-year position) PhD Candidate Apply for this job See advertisement About the position
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PhD Studentship in Physiology and Pharmacology Project title: Visualising Platelet Biogenesis: Intravital Imaging of Megakaryocyte Signalling in Real Time (UK fees only) Supervisors: Dr Alex Bye
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- Experience in image processing and/or - Familiar with rodent behavioural tests and/or - Experience in histology and/or - Familiar with the theory and preferably practical aspect of MRI. You will be responsible
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to reshape the paradigm of power system analysis and operation The opportunity to receive training and mentoring from world-leading experts *Candidates who have not yet been officially awarded their PhD will
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Research Centre for the Management of Agricultural and Environmental Risks (CEIGRAM) - Universidad Politécnica de Madrid (UPM) | Spain | 29 days ago
Research Infrastructure? No Offer Description Master’s degree in Agronomy. Research Line: Image analysis and early detection of pests and diseases in greenhouse crops. Where to apply E-mail ceigram.etsiaab
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) Positions PhD Positions Country Norway Application Deadline 13 Nov 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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to neurodegenerative disorders. Your PhD project specifically will focus on developing and applying a versatile high-throughput fluorescence imaging platform. In this function you will: optically design a microscope
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process (process-specific design) (2) Optimization of the LPBF process parameters to achieve desired microstructure and material properties, (3) In-depth materials, and property testing and (4) Prototype
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. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine learning models without moving sensitive or large