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devices into complex digital systems. Advanced expertise in machine learning and artificial intelligence for predictive and prescriptive urban data analysis. Experience in visualizing and analyzing spatial
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data collection approaches. Familiarity with or strong motivation to learn machine learning or advanced data analytics for pattern detection and forecasting in environmental data. Familiarity with
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, disability, ethnicity, familial status, gender (including transgender), gender identity or expression, genetic information, HIV/AIDs status, military status, national origin, pregnancy (false pregnancy
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. Responsibilities include working with digital signal processing, advanced filtering techniques, dynamic feature extraction, time-domain and frequency-domain analysis, signal fusion and machine learning to enhance
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records from satellite data, and/or improved methods of uncertainty characterisation, including the use of artificial intelligence and machine learning to improve or analyse satellite climate data records
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to communicate with other researchers and staff in person, on the telephone and by e-mail. Vision capable of viewing gauges, computer monitors, charts, forms, text and numbers for prolonged periods. Must possess
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are encouraged to Be Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and
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, Astronomy, or a closely related field is required. Experience with HPC systems, machine learning, and GRB monitor data analysis would be an advantage. Additional Information Applications must be submitted
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external) How to Submit Application Materials: To begin the application process, please send an email using the subject line “Postdoctoral Position in Machine Learning for Advancing Mental Health” to Tina
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Monitoring (LTVEM) in the hospital for management and diagnosis of epilepsy. The technology is built on brain computer interfaces equipped with a Spiking Neural Network (SNN) and aims at early detection