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Field
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within the Physical Vision Group (PVG, https://physicalvision.github.io/ ). This will involve closely collaborating with faculty, postdoctoral researchers, and PhD students, bridging foundational
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. • Contribute to the development of future grant applications. • Other activities as required. QUALIFICATIONS Required Qualifications • PhD completed within the last 5 years in Computer Science, Data Science
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) Application Deadline 17 Oct 2026 - 00:00 (UTC) Country Australia Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description NOMIS Foundation ETH Postdoctoral Fellowship The NOMIS
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core part of Vision Mātauranga: https://www.mbie.govt.nz/assets/9916d28d7b/vision-matauranga-booklet.pdf. • A willingness and the ability to support PhD, MSc, honours, and/or summer research students
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Robot Vision research environment. The role is aligned with the EPSRC OASIS Hub and will contribute to research in AI for advanced endoscopic imaging and computational imaging for interventional
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. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more information. All
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assigned by Supervisor. Requirements PhD in Computer Science or related field Expertise in computer vision and vision-language models Experience with ML evaluation metrics and benchmarking Proficiency in
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should possess: PhD/Ms/BSc in Computer Science, Artificial Intelligence, Electrical Engineering, or a related discipline. Strong research background in one or more of: Computer Vision Machine Learning Deep
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policy engagement on China through rigorous scholarship and meaningful public outreach. More information about CSKI and the fellowship program is available at https://www.mq.edu.au/faculty-of-arts/schools