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(“Autonomous System for Hybrid Hyperspectral-SAR Monitoring in Precision Agriculture”, Supervisor Prof. Hugo Hernández Figueroa, and “Development of Methodology and Robust Operational Algorithms for Hybrid
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optimization algorithms (e.g., SAT solving, constraint solving, MaxSAT, SAT modulo theories, Answer Set Programming, (Mixed) Integer Programming, ...). We offer a fully-funded postdoc position, initially for 12
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applications in the media change journalism, the public sphere, civic engagement and economic competition. We will develop and test new AI-applications to help solve problems such as disinformation, algorithmic
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properties of macromolecules, developing novel ways to combine quantum chemical methods and machine learning, developing quantum algorithms for computational chemistry on quantum computers, and applying
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optimization of optical imaging hardware, develop data acquisition software and algorithms for data processing, as well as perform phantom and human clinical studies. This candidate is expected to co-supervise
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sets and developing algorithms. You should be highly motivated, self-driven, and possess strong work ethics, team spirit, and excellent collaboration skills. You will be responsible for the collection
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algorithms at scale on ORNL's computational resources, including the Frontier supercomputer, addressing critical challenges in science and engineering. Communicate and coordinate experimental results with
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Requisition Id 15448 Overview: We are seeking a Postdoctoral Research Associate who will focus on creating innovative artificial intelligence algorithms for the trusted visualization of large
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Group , a leader in innovative multi-sensor atmospheric remote sensing from ground, airborne, and satellite platforms. Our group develops advanced algorithms and data analysis methods to address
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algorithms (convex/nonconvex, stochastic/robust, MPC) for real-time dispatch, frequency regulation, and DER coordination. Integrate data-driven and physics-informed approaches for state estimation, forecasting