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cutting-edge computer vision technology. Working closely with the Principal Investigator, Co-PI, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap
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will play a key role in automated wildlife identification and classification from trap camera images using cutting-edge computer vision technology. Working closely with the Principal Investigator, Co-PI
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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moulds electronic and computer engineers, computer scientists, AI engineers, interactive media and game development experts, software engineers, and information security specialists. We invite applications
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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sensor data under varying environmental conditions. Design computer vision and human-behavior analysis models for detecting personnel, posture, casualties, and hazardous situations, including operation in
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description FACULTY POSITIONS (AT ALL LEVELS) IN COMPUTER SCIENCE, COMPUTER ENGINEEERING AND
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: Architect and deploy machine learning and computer vision models directly onto onboard edge devices (e.g., NVIDIA Jetson) for real-time object detection, tracking, and autonomous decision-making. Proof
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simulations and live demonstrations. Job Requirements A Master's degree or higher in Computer Engineering, Computer Science, Data Science, Statistics, or equivalent. Strong theoretical background in statistics
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Requirements Have relevant competence in the areas of Cyber Security. Degree in Infocomm, Computer Science, Cyber Security, Computer/Electrical Engineering, Information Technology or equivalent. Possessing a