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-assisted tools leveraging large language models (LLMs) to support community-based fact-checking Designi and evaluate methods to improve the robustness of algorithms used in community-driven fact-checking
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for a candidate capable of developing ML models and optimization algorithms specifically designed for highly dynamic satellite communication (SatCom) systems that can handle networks of varying sizes and
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advanced mathematical frameworks and algorithms that accommodate the distinct operational characteristics of these mobility services while addressing their charging infrastructure needs. Project abstract
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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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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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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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environments (preferred). You possess the ability to conduct independent research and develop novel algorithms. You have strong analytical and problem-solving skills. You have a research-oriented mindset and
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presents significant challenges. These include enormous data bandwidths, sophisticated optical control, advanced rendering pipelines, and new algorithms that can tightly integrate physical hardware, sensors
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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