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Field
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well as collaborative research in the field of medical imaging. Specific research foci include the development of ultrahigh field MRI methods in terms of both acquisition parameters and processing, including software
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scanning confocal microscopy and calcium imaging in time-lapse, computational imaging approaches for analysis of images and movie recordings, analysis of the connectome to identify neural circuits
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for children and young adults. You are a creative and enthusiastic researcher with an MSc degree in Physics, Engineering or Biomedical Engineering, or similar. You have a clear interest in developing imaging
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guidelines into formal ontologies and knowledge graphs Design and develop modules for Medical Informatics Initiative (MII)/FHIR interoperability of the research prototype Work closely with clinicians and data
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22 Oct 2025 Job Information Organisation/Company Universidade de Vigo Department T13 Telematic Engineering Research Field Engineering » Communication engineering Researcher Profile Recognised
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Research Centre for the Management of Agricultural and Environmental Risks (CEIGRAM) - Universidad Politécnica de Madrid (UPM) | Spain | 8 days ago
@upm.es Requirements Research FieldAgricultural sciences » Agricultural productsEducation LevelMaster Degree or equivalent Skills/Qualifications • Experience in handling images • Experience in using
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working practice, and strong team working skills. Admission Requirements Master or Diploma degree in Computer Science, Computer and Information Engineering, Software Development, or equivalent fields
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Max Planck Institute for the Structure and Dynamics of Matter | Hamburg, Hamburg | Germany | 26 days ago
within a Research Infrastructure? No Offer Description The International Max Planck Research School for Ultrafast Imaging and Structural Dynamics in Hamburg, Germany, offers a structured PhD program
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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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areas: scientific programming and data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or biophysics Familiarity with