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Field
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of the professor(s) PhDs: Elga Patrícia Maximiano Ferreira . Financial components of the fellowship: Monthly maintenance allowance, in the amount of €701.12, according to the table of values of FCT, I.P. (https
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activities. You must have a PhD or equivalent in Biology, Palaeontology or another relevant subject area and proven knowledge of mammalian anatomy and evolution. Experience in working with morphological image
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, original forms of identification for employment verification via the Federal I-9 employment verification process. A list of acceptable documents can be seen here: https://www.uscis.gov/i-9-central/form-i-9
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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for future career success, but also have a good quality of life and wellbeing, thus supporting a flourishing society. For more details, please view: https://www.cares.cam.ac.uk/research/clic/ We are looking
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in a study cycle conferring an (PhD) degree in Arts or related areas. Candidates for the Research Fellowship, after selection, to start contracting the fellowship, must enroll in the doctoral program
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-time research experience since their PhD completion. We are looking for candidates with a PhD and a strong background in PET imaging, particularly with demonstrated expertise in the processing and
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: https://www.jobbnorge.no/en/available-jobs/job/294558/phd-research-fellow-in-deep-learning-for-imaging-of-marine-ecosystems Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294558/phd
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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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learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image analysis, that is medical images that evolve over