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Field
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(but are not limited to) Computer Science, statistics, mathematics, automation, informatics, and Engineering. Experience in deep learning, machine learning and medical imaging processing Programming
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immune responses By combining transcriptomics, immunohistochemistry, advanced imaging, and physiological assays across, we aim to elucidate the fundamental processes underlying the evolutionary success and
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/Qualifications We welcome applications from researchers who: Hold a PhD in neuroscience, biomedical sciences, physics, engineering, or a related field Have experience in brain imaging (e.g functional ultrasound
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sophisticated machine learning tools for image processing Experience in mathematical modelling Knowledge in comparative neuroscience (comparative vertebrate neuro) Proficiency in basic computer packages (eg
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WordPress (40%) Specific knowledge in photographic image processing (30%) Specific knowledge in text production and proficiency in English (CET) (30%) Final classification (NF) will be calculated as follows
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Master’s degree in Education or a related field. Be enrolled, or meet the conditions to enrol, in a study programme leading to a PhD in Education. Be fluent in Portuguese and English, both spoken and written
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: PhD degree in Computer Science, Electrical Engineering, or a closely related field Strong research background in computer vision and deep learning Solid experience with multimodal learning, segmentation
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Procedure Individual Licence (ASPA personal licence) For appointment at grade 7: Essential: A4 Normally Scottish Credit and Qualification Framework level 12 (PhD) plus track record of emerging independence
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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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We are looking for a highly motivated PhD candidate interested in AI-based methods, including machine learning and language technologies, for the integration and analysis of clinical, advanced data