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related field, and experience in one or more of the following areas: multiphoton imaging, optogenetics, calcium imaging, and / or in vivo electrophysiology. Applicants without prior experience in
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more. The postdoc fellow will be working on a wave-function picture of open quantum dynamics, including the effect of measurement. The applicant should be a creative and motivated researcher with
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | 21 days ago
vivo models of PD Apply and further develop methodologies such as disease modeling, virus-mediated gene delivery, behavior, immunohistochemistry, tissue clearing and 3D imaging, image analysis, spatial
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Astrophysics (MPO), Stellar and solar Physics, Signal and Image processing (Signal), Theory and Observation in Planetology (TOP) and Turbulence, Fluids and Plasma. It is the birthplace and remains a world leader
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fluid dynamics and vascular modeling in microenvironments Skills in data analysis and image processing (e.g., Python, R, ImageJ) Ability to mentor junior researchers and contribute to team leadership What
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(R3) Positions Postdoc Positions Country Brazil Application Deadline 3 Oct 2025 - 23:59 (America/Sao_Paulo) Type of Contract Not Applicable Job Status Full-time Hours Per Week 40 Offer Starting Date 1
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room-temperature exciton–polaritons, partly achieved by the team of Jesus Zúñiga-Pérez, has opened the way to practical applications of polaritons. Exciton–polaritons promise faster data processing
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systemic infectious processes, immune responses, and evaluating therapies, refinement measures to reduce stress and improve welfare in experimental animals are underexplored. In this 3RTG, we will address
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collaboration with Olof Lagerlöf’s group. The postdoc will image (and influence with opto-chemogenetics) the network representation of stimuli of different economic/hedonic value and its plasticity with two
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implement cutting-edge AI solutions for real-time, image-guided medical applications, with a focus on advanced robotics. You will work directly with clinical data to design robust, efficient deep learning