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present on expedient osseous tools. This methodological breakthrough relies on discriminant analysis of surface textural data (ISO 25178 and SSFA) acquired by confocal microscopy combined with image
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objective of this project is to compare the modern philosophy of Bildung and the contemporary paradigm of the Learning Society (LS) by systematically analyzing their homological structures. Through
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 10 days ago
Job Code: 27-25 Job Offer from September 30, 2025 The Max Planck Institute for Multidisciplinary Sciences is a leading international research institute of exceptional scientific breadth. With
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 9 days ago
opportunity in computational inverse problems in the context of the ERC-StG European project Incorwave which aims to develop advanced numerical and mathematical strategies for passive imaging. This postdoctoral
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decide the fate of their RNAs - whether to translate, store, or degrade them. Using biochemical reconstitution, fluorescent labeling, and single-molecule imaging, you will explore how molecular machines
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very-long-baseline interferometry (VLBI) system, named VLBI Global Observing System (VGOS) by (1) deriving structure images of the Active Galactic Nuclei (AGNs) directly from VGOS observations, (2
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physical characterization techniques (differential scanning calorimetry, dynamic light scattering, small angle neutron and/or x-ray scattering) to characterize the DIBs; and (3) Develop/implement image
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Molecular Imaging and Radiology (MIRA) of the Faculty of Medicine & Health Sciences, is looking for a full-time (100%)postdoctoral scholarship holder in the field of preclinical radioligand development
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, and sensor data processing algorithms; implementing and testing ROS nodes, embedded controllers, and closed-loop control routines on prototype hardware; preparing technical reports, delivering
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imaging, multi-modal clinical and omics data, and explainable AI (XAI) for the prediction of hepatocellular carcinoma (HCC). Your research will directly contribute to early detection and risk stratification