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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
of critical thinking Experience with photonics, fluorescence, imaging or biochemical methods is helpful Our offer Highly motivated team Flexible working hours World-class institute with outstanding
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for Studying Metabolic Plasticity (ECR 5) For further information please visit: https://www.umg.eu/en/potenziale-entfalten/ecr What we offer: Generous support (your own position, a postdoc (1.0), a PhD student
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histological validation within murine cancer models. We offer an association with the Collaborative Research Centre 1450 “Insight – Multiscale imaging of organ-specific inflammation” graduate school
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, we are looking forward to your scientific support at the Clinic for Radiology! We are seeking a highly motivated PhD student to join our interdisciplinary research team working on multimodal imaging
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. The letters will then be added to your application in our system and forwarded to the appropriate persons. Please ensure that you only use .pdf files, Word documents and images in .jpg format. Please also
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cutting-edge research project within a highly interdisciplinary and international team and a supportive research environment Access to state-of-the-art imaging and analytical facilities Opportunities
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and IT develop innovative radiopharmaceuticals and novel tools for functional characterization, improved imaging and personalized treatment of tumors. The Department of Department Life Science
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, you need to develop and apply methods that enable the recognition of phenological stages of allergenic plants on images. Then, the phenological development of these species shall be modelled based
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: Microscopy, histology, and image analysis to phenotype root anatomy. Plant and root physiological measurements to determine the function of root phenotypes. Genome-wide Association Studies (GWAS) and
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architectures and principles from Bayesian neural networks and biological sequence models, including large DNA and protein language models. The project also aims to develop a prototype federated learning