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Dipartimento di Ingegneria dell'Informazione - Università degli Studi di Padova | Italy | about 2 months ago
/ies of residence: OTHER Eligibility of fellows: nationality/ies: OTHER Selection process https://www.unipd.it/bandi_list Website for additional job details https://www.dei.unipd.it/bandi/termine/395
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the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/ ) About the project/work tasks: This position is part of: 19 PhD Fellowships available in Digital Endocrinology in the Marie
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project on the release of hormones, neuropeptides, and neurotransmitters by exocytosis, which is mediated by a vesicular fusion process whose mechanisms are well established. However, the mechanisms
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imaging of energy storage materials, with the focus on detection of light elements and monitoring of electrochemical processes. The research will be conducted primarily at the accelerator facility
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, diagnosis, drug response and health monitoring. Research in precision medicine is expected to use existing strong assets in Sweden and abroad, such as molecular data (e.g. omics), imaging techniques
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, a PhD, who has been selected at the end of the recruitment process for a professorship at Polytechnique, to complete her training with a postdoctoral fellowship, here or abroad. Upon recommendation by
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work environment with social and psychological safety. What you bring PhD in neuroscience, biomedical sciences, psychology, medical imaging, epidemiology, or related field. Experience with clinical
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, microscopy, image analysis, and molecular biology. Requirements To be eligible for this position, you must hold a PhD or a foreign degree deemed equivalent in systems biology, biophysics, molecular biology
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Facilities, Sahlgrenska Akademin in Gothenburg, Sweden. Selection process For more information regarding the selection process go to: https://www.gu.se/om-universitetet/jobba-hos-oss/hjalp-for-sokande#S%C3%A5
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Learning and Computer Vision Objetives: This work aims to study, develop and implement computer vision methods to detect and classify areas with imaging alterations from MRI and CT scans