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https://sheffield.ac.uk/cs For informal enquiries about this job, contact Dr Jefersson A dos Santos, project lead, at [email protected] Next steps in the recruitment process It is anticipated
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of Biomedical Engineering and Imaging Sciences (https://www.kcl.ac.uk/bmeis ) is a cutting-edge research and teaching School dedicated to development, translation and clinical application within medical imaging
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Magma Research Associates / Magma Research Fellows to develop and maintain the Magma computer algebra system (http://magma.maths.usyd.edu.au/magma/ ). These positions are based at the University
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pain and sensory processing differ between females and males, how physiological states such as pregnancy remodel neural circuits, and how maternal experiences can shape sensory function across
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
world. Position Summary This Postdoctoral Research Associate will conduct advanced research in artificial intelligence, machine learning, computer vision, and medical image analysis. The position will contribute
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Therapeutic Radiological Physics Preferred Qualifications: PhD Graduation from a CAMPEP-approved Medical Physics Residency Program Knowledge of Eclipse, Brainlab, Oncentra, CRAD Surface imager, proton therapy
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no later than three years before the beginning of the contract. Selection process CV, cover letter and copy of PhD degree to be sent by email mentioning reference of job offer at : drh-recrutement
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to create knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position As a PhD Candidate with us, you will help turn early railway
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early metabolomic disruptions, followed by the genetic and biochemical dissection of the mechanisms underlying these alterations. The project takes advantage of recent transcriptomic and imaging data