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, modulation classification, sensing, and adaptive spectrum optimization in diverse operational environments. Your work will focus on modeling and algorithmic aspects related to the development of highly
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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
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genomic graphs. The project will also deliver efficient algorithms to train these models under budget and time constraints, facilitating flexible adoption of the methods. The project is carried out in close
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 4 hours ago
to): Develop machine learning algorithms that utilize fire products from geostationary satellites to better represent fire evolution and variability Develop machine learning emulators to represent forward
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of computational biology, Genomics, machine learning, and data science, contributing to the development and evaluation of advanced algorithms for analyzing large-scale biological datasets. This role is ideal
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and BDI Systems. He/she will work under the supervision of the center's executive president. Your main tasks: Design, develop and apply NLP algorithms in various projects. Contribute to the supervision
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description languages. Develop and optimize EDA workflows for processor and accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for
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solvers • Implementing and analysing online optimisation algorithms for real-time grid balancing • Liaising with project partners (NESO and University of Strathclyde) Essential selection
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applications for a Post-Doctoral Associate position, in the area of Quantum Algorithms. The candidate is expected to conduct research in computer science focusing on the combinatorial aspects of quantum
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The undergraduate research assistant will support a faculty-led research project examining how algorithmically generated student groups influence compatibility, stigma reduction, and interaction quality in first-year