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2 Oct 2025 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique et des Systèmes Research Field Computer science Mathematics » Algorithms Researcher Profile First Stage
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, telecommunications or related field. Other requirements include Strong background in communication theory, signal processing, and wireless communications, Extensive experience in physical (PHY) layer algorithm design
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Center’s mission is to create the theoretical, computational and algorithmic paradigms that will enable us to understand the programs of life and how they connect across scales, from proteins to cells
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and Mission Science team located at ESTEC (Noordwijk, Netherlands) to align the development of AI-driven methodologies and algorithms with the CHIME mission. Technical competencies Knowledge relevant
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electron beams, advanced beam-manipulation for precise electron-beam shaping, and ML for accelerator science. Responsibilities Develop and deploy ML algorithms for autonomous operations and optimization
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learning algorithms Healthcare facility design and research Knowledge, Skills, and Abilities: Excellent verbal and written communication skills, including publications in peer-reviewed journals. Strong
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gene gain/loss events, horizontal gene transfer, and functional diversification within gene families. You will apply statistical models and machine learning algorithms to identify associations between
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National Aeronautics and Space Administration (NASA) | Cleveland, Ohio | United States | about 6 hours ago
@orau.org Qualifications Background in engineering, computer science, or a similar field. Background in software tools such as Matlab, Python, and C/C++ Experience developing machine learning algorithms
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increasing environmental awareness. However, most existing hearing aid algorithms optimize for only one of these objectives at a time, often at the expense of the others. To enhance hearing aid performance
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algorithm controversy game. Design Studies, 91, 101245. Hicks, B., Kitto, K., Payne, L., & Buckingham Shum, S. (2022). Thinking with causal models: A visual formalism for collaboratively crafting assumptions