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the central hypothesis of these infections causing general stress responses and behavioural changes, which can be assessed on metabolic level or by video observation and artificial intelligence analysis
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knowledge and skills in the following areas: Life cycle analysis (in-house training possible at the start of the contract) Digital system consumption Networks and telecommunications Audio and video coding
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Description You will: * Lead MEG head-cast data collection for a visuomotor reaching/interception study, ensuring robust synchronization with video-based kinematics and eye-tracking, and enforce rigorous
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of developing cutting-edge deep learning models for real-time image and video analysis (e.g., segmentation, object tracking, reinforcement learning), with applications to medical imaging and robotic systems. In
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Translating deep learning models into clinical settings Experience developing deep learning models for real-time image/video segmentation, object tracking, 3D reconstruction, super-resolution. Have a passion on
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Full Time, Fixed Term (31/07/2028) The closing date for applications is 23.59 on 10 October 2025 Interview Date : 20 October 2025 By reference to the applicable SOC code for this role, sponsorship
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mathematical frameworks for multimodal integration, advance video transformer architectures for temporal-spatial dynamics, and develop few-shot learning methodologies for ultra-low-resource scenarios with only
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to create knowledge for a better world. You can find more information about working at NTNU and the application process here . ... (Video unable to load from YouTube. Accept cookie and refresh page to watch
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formats: video recording, online or onsite. The question based interview will evaluate the match between the candidate’s profile and the requirements for the position, including the technical and personal
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Reading UK Contract: Full Time, Fixed Term (31/07/2028) Job reference: SRF51665 By reference to the applicable SOC code for this role, sponsorship may be possible under the Skilled Worker Route. Applicants