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Research Associate will contribute to developing and/or applying artificial intelligence, machine learning, and image segmentation and/or data science-based methods to address cutting-edge topics, including
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advanced imaging to dissect the cellular signaling and regulatory networks that control photosymbiosis between cnidarian hosts and their microalgal symbionts. The Project - PhagoPhoRe This position is
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THIS VACANCY IS OPEN TO INTERNAL APPLICANTS ONLY About us: The School of Neuroscience is UK’s 2nd largest Neuroscience school with over 500 researchers and 200 PhD students. It is one of three
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visual dimensions in the context of face, animacy, and object representations more generally. We collect and analyse human behavioural and brain imaging (fMRI and M/EEG) data. We also analyse macaque
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
biomedical imaging applications Your profile Master’s degree or PhD in Physics, Optical Engineering, Photonics, Quantum Engineering, Biomedical Engineering, or a closely related field, with a focus on quantum
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and tracking in LEO constellations, and monostatic and bistatic SAR imaging using communication waveforms Design and evaluate self-interference cancellation (analog/digital) and synchronization
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) can be used safely to image and regulate mood state in a closed loop fashion in healthy volunteers as well as patients with prior history of brain damage, using state-of-the-art neuroimaging methods
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PRIMARY DETAIL • Salary Package: $109,272 – $117,108 per annum ((Level A.6–A.8, PhD Awarded Rate), or a higher salary may be considered for candidates with significant relevant experience, plus 17
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methodological reference framework for functional measurements on liver and heart sections. Skills and Requirements Excellent Master’s degree and PhD in biology, nutrition science, medicine, or a related
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with