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algorithmic, hardware, and platform engineering teams. What you will do You actively shape imec’s research and engineering roadmap by tackling the following core architectural challenges: Architecting endtoend
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embedded AI-based algorithms. The applicant should: have a Master’s degree in Electrical Engineering, be ranked within the top 10% of their class in MSc and BSc, and have exceptional grades, have a strong
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‑world adoption. Role Overview We are seeking a postdoctoral researcher to define and execute an ambitious research agenda at the intersection of generative AI and algorithm-hardware co‑design for next
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several related areas of expertise: generative AI for robotic planning and control, cognitive control, distributed perception and control, and HW-SW co-design of algorithms. Our research is applied across
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Engineer in Underwater Perception, you play a pivotal role in shaping the future of energy-efficient AI algorithms for underwater perception. What you will do Identify research and technology gaps
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. Our research spans several related areas of expertise: generative AI for robotic planning and control, cognitive control, distributed perception and control, and HW-SW co-design of algorithms. Our
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; Real-World Validation: Deploy and benchmark your algorithms on our autonomous vehicle, mobile robots, and UAV testbeds. You will: publish in CVPR/ICCV/ECCV, NeurIPS/ICLR, and leading IEEE journals
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more manufacturable optical systems. The emphasis is on system-level thinking, design automation, and practical relevance, rather than narrow algorithmic optimization. A realistic optical system (e.g. a
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functionality. Your work will involve designing advanced algorithms that efficiently utilize UWB signal features (RSSI, channel impulse response, phase and amplitude data, Doppler maps,..) to support both high
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of this PhD project is to develop novel 4D image reconstruction methods for X-ray imaging where the object changes over time. In particular, the goal is to develop efficient 4D reconstruction algorithms