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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
. Dr. Helmut Grubmüller, invites applications for a PhD Student or Postdoc (f/m/d) for the project Theory and Algorithms for Structure Determination from Single Molecule X-Ray Scattering Images Project
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. Disseminate research through high-impact publications and conference presentations. Requirements: PhD (or near completion) in Imaging Science, Computational Biology, Bioinformatics, Machine Learning, Data
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molecular imaging research program. This platform will support translational studies mainly in oncology, through quantitative multimodal imaging (PET-CT, SPECT-CT, optical imaging, autoradiography
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Qualifications PhD in Neuroscience or other related field Experience in in vivo dosing (IV,IP, SC), mouse brain stereotactic surgery, in vivo two photon imaging, image analysis Qualified applicants must be
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assays) and high-resolution imaging approaches and quantifications from both mouse and human brains; mouse brain regional dissections; western blotting; and experiments in various in vitro culture systems
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the mechanosensitive processes and the mechanical properties of tissues that drive tumor malignancy and anti‑tumoral immune responses. This multidisciplinary project will combine: Biophysical techniques and image
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Intervention invites applications for a two‑year postdoctoral fellowship within the project AI‑Driven Medical Imaging. The position is expected to start on 1 September 2026 or as agreed. The fellowship is funded
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fundamental discovery to patient care. Our laboratory focuses on advanced label-free optical technologies for disease detection and characterisation. We develop fibre-optic and multimodal imaging systems
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As part of the UKRI funded `Glaciers and Ice Sheets in a Warming World' project, we have an exciting opportunity for a postdoctoral researcher who has expertise in image analysis to join the project
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for the analysis of hyperspectral imaging data applied to pictorial layers, based on coupling physical radiative transfer models (two-flux and four-flux approaches) with machine learning methods. The researcher will