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PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (deep learning, computer vision, robotics) Number of awards: 1 Award information: Fully funded PhD studentship covering Home
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for data-efficient vision foundation models. Foundation models in computer vision currently rely on massive datasets and brute-force scaling. This leads to high data requirements, hidden biases, limited
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performance (10–50 Hz) on hardware with constrained memory, power and compute. The project will investigate training, adapting and deploying compact Physical AI models efficiently. Work may cover vision
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Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position
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scholarship for this research and enter “PhD Scholarship in Communication and Navigation for People who are Blind or have Low Vision” as the scholarship name under Research Program Funding of the application
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Portal or send them to the PGR Admissions team at [email protected] . Please quote the reference: SciEng-DTA Jan 2027-AD-Micro Expression Vision Application link: PhD Computing and Digital Technology
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, computer vision, and medical robotics while working within the Medical Robotics Laboratory at the University of Newcastle. PhD Scholarship details Funding: Funding: $38,938 per annum (2026 rate) indexed
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and illegal logging detection. Working at the intersection of computer vision, deep learning, geospatial analysis and remote sensing, the postholder will collaborate closely with academic and
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).The PhD candidate is expecting to assisting in teaching and help in laboratory on the related topic. Applicants should fulfil the following requirements: A Master's degree in computer engineering, computer
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, computational biology, statistics or a closely related field. You have strong programming skills, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision