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journals. Close collaboration with team members and colleagues. Essential qualifications: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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: 01.10.2025 Application deadline: 03.09.2025 Tasks Execution of experimental work in a mouse model of cortical multiple sclerosis Application of in vivo imaging and quantitative analysis methods Investigation
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Max Planck Institute for Medical Research, Heidelberg | Heidelberg, Baden W rttemberg | Germany | about 20 hours ago
Job Code: 15/2025 Job Offer from September 09, 2025 We, the Max Planck Institute for Medical Research, are one of 84 institutes and research centers of the Max Planck Society (MPG
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learning, image analysis, and advanced computing to study relationships between structure and function. Keywords: Human Brain, 3D Atlas, Deep Learning, Temporal Lobe, Brain Function Entry Requirements
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, imaging or biochemical methods is helpful. OUR OFFER Highly motivated team Flexible working hours World-class institute with an outstanding working environment The payment is based on the TVöD guidelines
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for biology and healthcare; then, the Chair of Biological Imaging (CBI) at the Technical University of Munich (TUM), and its integrated Institute of Biological and Medical Imaging (IBMI) at the Helmholtz
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to characterize biodegradable Mg alloys containing a Long Periodic Stacking Ordered (LPSO) phase, developed for medical implant applications. You will be responsible for establishing a correlative
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Description Main tasks You will join the Institute of Medical Systems Biology and the bAIome Center for Biomedical AI ( baiome.org ) to complement our lively and enthusiastic team of machine
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, catalysis studies - in particular electrocatalysis and Python programming Experience within the following fields is highly beneficial: Transmission electron microscopy, Electrochemistry, Image analysis, Big