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about working at NTNU and the application process here. ... (Video unable to load from YouTube. Accept cookie and refresh page to watch video, or click here to open video) About the position To be able
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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diagnostics (theranostics), focused ultrasound (FUS), and molecular imaging (PET/SPECT). The PhD candidate will be responsible for conducting preclinical studies using animal models of glioblastoma, including
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influence brain and heart health. Responsibilities will involve recruiting participants, screening participants for eligibility, scheduling participants, collecting physiological and brain imaging data (MRI
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or directly inside the cell. This approach requires biochemistry or cell biology for the sample preparation and scripting skills for the ET data processing. For more information, please read PMID33762348
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, you will investigate temporal changes in subarctic benthic communities, their trophic interactions, and the impact of larval supply. This will involve processing and analysing samples such as
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measuring stand for the collection of hyperspectral data on a test field Collection of imaging data and creation of a database Establishment of a data processing routine for pre-processing the hyperspectral
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 3 months ago
Job Code: 18-25 Job Offer from June 04, 2025 The Department of Prof. Dr. Stefan W. Hell invites applications for a PhD position exploring AI approaches in optical science, molecular imaging and
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. Train in cryo-TEM sample preparation, imaging, and interpretation, leading Nanoworx’ efforts in this area. Analyze and interpret data, delivering clear and concise reports, and contribute to team
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
to improve the capacity of these microbes for efficient, high-yield bioconversions from CO2 and P2X feedstocks, such as methanol, formate, and hydrogen. Our ultimate goal is to prototype and develop next