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equivalent foreign degree, obtained within the last three years prior to the application deadline Experience with simulation frameworks, system-level performance evaluation, or machine learning, is highly
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looking for a postdoctoral researcher in the area of Generative AI. VITA research interests lie at the intersection of Computer Vision, Machine Learning (Deep Learning), and Human-Robot Interaction
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 6 days ago
-series. Experience exploring machine learning and deep learning techniques for geospatial applications is highly desirable to effectively engage with Earth observation foundation models. Technical
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microscopy, tissue culture, biochemistry, physiology, or biophysics. Enthusiasm and commitment to pursue novel research areas and develop new techniques and approaches. Team player with an interest in learning
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no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining. ● Demonstrated research expertise in federated learning, differential privacy, machine
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. • Very good knowledge of Python • Experience with machine learning libraries such as PyTorch, JAX, TensorFlow or equivalent • Knowledge of micromagnetic simulations • Interest in inverse-design methods
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: A doctorate in a Machine-Learning related field A deep knowledge of Control Theory, both classical and deep learning based A solid publication record in top level ML venues such as NeurIPs, ICML, and
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position within a Research Infrastructure? No Offer Description Activities and context: The fellow will develop machine-learning interatomic potentials (MLPs), trained on density functional theory-DFT data
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science and/or artificial intelligence. You have gained knowledge of various machine learning techniques, particularly artificial neural networks and deep learning and would like to further develop
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well as machine learning and multivariate decoding of neuroimaging data to predict subjective experiences and individual differences. Successful candidates will be supported in building a research program at the