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Are you interested in challenging deep learning at its core? And specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision
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specifically, do you want to perform cutting-edge research and develop novel advances in hyperbolic deep learning for computer vision? Then check out the vacancy below and apply for a PhD position in this
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This PhD project focuses on advancing computer vision and edge-AI technology for real-time marine monitoring. In collaboration with CEFAS (the Centre for Environment, Fisheries, and Aquaculture
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Job Description If you are passionate about stem cell biology and want to make a real difference for patients suffering from vision loss, this PhD position is for you. At DTU Health Tech, we offer a
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Mar 2026 - 22:59 (UTC) Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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DTU Tenure Track Researcher in Low-Noise Supercontinuum Lasers and Supercontinuum Laser based Opt...
: Research experience Experience and quality of teaching Research vision and potential International impact and experience Societal impact Innovativeness, including commercialization and collaboration with
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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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related disciplines Quantitative imaging, data analysis, or computer vision Numerical modeling of biological systems or continuum mechanics Machine learning/AI, particularly explainable AI (XAI) Hands
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-NanoThings, where sensing, actuation, and computing processes are tightly coupled to pervasively, perpetually, and precisely sense, process, control, and exchange health information of the body in real-time to
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by detecting and predicting threats such as pests, diseases, and environmental stress in line with the UK Plant Biosecurity Strategy. The project harnesses computer vision, deep learning, and large