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researcher will work at the interface of root developmental biology, 3D modeling, network and graph theory, and data analysis, in close interaction with biologists, modelers, and computer scientists (INRAE
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a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. Your Job: Develop 3D+t image reconstruction methods in a cell microscopy setting using image sequences
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programming (particularly IDEA) or image reconstruction Experience of computational modelling and simulatxion Knowledge of statistical and/or machine learning methods e.g. for 3D imaging data for applications
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. ACTIVITIES Medical image processing and 3D model reconstruction Computational model development using mechanical properties of biological tissues (from the laboratory’s work) Scientific result dissemination in
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Your Job: We are looking for a PhD student in machine learning to work within a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. Your Job: Develop 3D+t
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Signal Decoding for Neural 3D Human Motion Reconstruction and Transfer Using Latent Diffusion Models” (2026–2029) at the University of Oulu. The project develops next-generation non-invasive brain–machine
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, with the goal of linking the photochemical properties of photosensitizers to the structural and functional responses of the skin tissue. Culture human skin cells in 2D (monolayers) and 3D (reconstructed
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-manipulation generation, balancing regulation, physical interaction and teleoperation control. We are looking for an exceptional and highly motivated scientist to work on situational awareness systems for mobile
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. Further develop and maintain our tomographic reconstruction and processing pipeline, reconBlazer. Carry out independent research in 3D image analysis using data from full-field X-ray imaging experiments
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well as NHS colleagues at the West of Scotland PET Centre. This includes physicists, technicians, radiochemists, image analysts, research scientists, and clinical researchers. You'll also collaborate with teams