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Field
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applicant will have a PhD in vision science, computer science, or a related field. Experience in cloud-based and mobile image processing for rapid object and face recognition and in use of head-mounted eye
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The position A PhD position is
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if you are highly motivated, have interests in computer vision and neural networks, and want to both contribute to new advances in a field with real world applications. Your research focus will be
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on Smart Fibre-Optic High-Power Photonics (HiPPo). The HiPPo programme (https://www.hippo-laser.co.uk/ ) is focused on understanding how to control the properties of fibre lasers, to go beyond the “fixed
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on Smart Fibre-Optic High-Power Photonics (HiPPo). The HiPPo programme (https://www.hippo-laser.co.uk/ ) is focused on understanding how to control the properties of fibre lasers, to go beyond the “fixed
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. Admission to a PhD program is a prerequisite for employment, and the program period starts on commencement of the position. The PhD candidate shall participate in the university’s organized research training
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PhD Fellow in Anthropology: Bushmeat, Infrastructure and Zoonotic Risk in Africa–China Contact Zones
). The position is for a period of three years. The objective of the position is to complete research training to the level of a doctoral degree. Admission to the PhD programme is a prerequisite for employment, and
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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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computer science/statistics/applied mathematics/electrical engineering can also be considered given that the candidate has formal competence in machine learning and/or image analysis/computer vision Foreign
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Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related