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combinations of theoretical physics, mathematics, and machine learning. While machine experience is not a strict requirement for the job, we anticipate that the strongest candidates will have clear research
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, project management, and presentation skills Proficient with computer applications and programs associated with the position (i.e. Microsoft Office suite) Strong attention to detail and follow-up skills
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a postdoc in the field of Acoustic Sensing and Machine Learning for Sustainable Battery
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Qualifications Hands-on experience integrating hardware + software for robots (arms, mobile, mechatronics) and real-time control. Experience in computer vision, multimodal perception, or foundation models (VLMs
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such as computed tomography (CT) and x-ray phase contrast imaging (PCI). Perform laboratory duties such as setting up instruments, perform calibrations and acquire data. Participate in the development
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/ Deep Learning (particularly Computer Vision or 3D perception) Verification & Validation (V&V) of advanced algorithms, software or systems Formal Methods Safety Engineering / Safety-Critical Systems
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and real-time data acquisition systems. Participate in testing and deployment of UAV demonstrators at UM6P and OCP sites. Methodology: AI Development: Reinforcement learning, computer vision, and sensor
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will design and implement novel computer vision and machine learning methods for “sensorized” cameras that extract medically relevant features without transmitting raw video. You will evaluate algorithms
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vehicle validation. Design and implement machine learning models that capture the complexity and variability of real-world traffic situations, including unusual pedestrian behaviors, edge cases, and multi
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position, available until December 2027. Flexible work arrangements can be negotiated with the right candidate. Be part of the Australian Institute for Machine Learning – the largest computer vision and