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scale radar datasets with high quality labels remain scarce. In this PhD project, you will investigate foundation models for automotive imaging radar. The goal is to learn general radar representations
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combines microfluidics, bubble physics, and ultrasound signal processing to bring nanobubble imaging closer to clinical use. You will collaborate closely with a fellow PhD candidate, a postdoc, and a
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will find more information about working at NTNU and the application process here. About the position We have a vacant 100% PhD position in the MRI Physics Group at the Department of Physics, NTNU
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18th October 2026 Languages English English English The Department of Physics has a vacancy for a PhD Candidate in AI-assisted medical imaging with MRI Apply for this job See advertisement Are you
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deep learning, computer vision, medical image analysis or unsupervised learning is an advantage. English language skills, both written and spoken Qualification requirements PhD stipends are allocated
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Computational Imaging for High-Throughput Applications (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of the Leiden Institute
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Engineering » Biomaterial engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 25 Sep 2026 - 17:00 (Australia/Adelaide) Country Australia Type of Contract
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PhD in Computational Imaging for High-Throughput Applications (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of
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The successful PhD candidate will undertake research in the following areas: Develop deep learning algorithms for autonomous robotic navigation using dual-view image fusion and shadow-based visual perception
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increasing pressure to minimise global warming impacts over the building’s new life cycle. As a PhD researcher within the Horizon Europe project ReEnsemble, you will investigate how decisions about adaptive