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We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training costs and energy requirements of state-of-the-art deep learning models significantly, while...
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Sensor Fusion: Strong background in processing and fusing data from cameras, LiDAR, radar, or other sensors for robust autonomous system perception ML Engineering and Experimentation: Proficiency with
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of prof. Leprévost’s group at the Laboratory of Algorithmics, Cryptology and Security.
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multimodal data. Your responsibilities include: Developing and applying machine learning, deep learning, and LLM-based methods to multimodal clinical datasets e.g. EHR, imaging, omics, sensor data Designing
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technologies (fiber-optic sensors, DIC), and computer science (machine learning tools) in collaboration with de department of Physics. The aim of the BriCE project is to develop a novel bridge monitoring
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composed of highly motivated, active members. The group benefits from advanced research infrastructure, including the Computer Vision Lab, equipped with state-of-the-art visual sensors and acquisition
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, equipped with state-of-the-art visual sensors and acquisition systems, along with the Zero-G Lab, a unique facility designed to emulate proximity operations under space-like conditions. In addition, CVI2
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applications, GIS integration, sensor networks, OpenBIM, Linked Data (ii) Contribute teaching to the bachelor and master programmes of the department, e.g., in: Construction and Project Management (Bachelor) BIM
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validation (V&V) techniques for space systems, software and algorithms with a focus on specific challenges of space-borne perception and proximity operations uncooperative spacecraft . Develop novel methods
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/sigcom In addition, SIGCOM hosts the following experimental facilities: 6GSpaceLab: Real-world validation of advanced communication algorithms CommLab: Real-time wireless testbeds for DSP in satellite and