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. Familiarity with frameworks such as TensorFlow and Keras, as well as libraries including Scikit-learn, NumPy, and pandas; - Experience with machine learning models such as Extreme Learning Machine (ELM
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and Liu, Supervised learning in physical networks: From machine learning to learning machines, PRX 11, 021045 (2021) [2] Stern and Murugan, Learning without neurons in physical systems, Ann Rev Cond
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programming and instrument control using Matlab, Python, Labview etc Machine / deep learning expertise Strong analytical skills and ability to work in a multidisciplinary team Excellent communication and
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 2 hours ago
to constrain the representation of aerosols in the NASA GEOS Earth System Model. Activities that would be involved in this project include (but are not limited to): Implement machine learning transfer learning
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or machine learning applied to brain signals would be an advantage. We are seeking a highly motivated, rigorous and inquisitive researcher, ready to commit to a project at the interface between basic and
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, disability studies, or inclusive design Experience with participatory design or community-engaged research Technical skills in prototyping, data analysis, or machine learning are a plus Experience with human
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025 BRIDGES project GenePPS, which investigates how machine learning can enable prediction of gene perturbation
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flexibility. Responsibilities include conducting behavioral neuroscience experiments—including vapor self-administration and operant conditioning tasks (such as attentional set-shifting and reversal learning
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position within a Research Infrastructure? No Offer Description Activities The fellow will be expected to research the relationship between these technologies (big data, machine learning, and the entire