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or machine learning Experience with Swift development and/or strong willingness to work within the Apple development ecosystem Experience in edge AI, model optimization, or deployment of AI models
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in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
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before starting—in computer science, electrical or computer engineering, information science, or a closely related discipline. Less than 5 years post receiving the Doctoral degree. Meet the mandatory
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Requirements Standing or sitting up to 8 hours/day, lifting <30 lbs, may view computer up to 8 hours/day. Shift Generally Monday – Friday, 8a-5p with some flexibility Job Summary This position is designed
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, machine learning, generative AI and related fields as part of the DataSig II grant “High order mathematical and computational infrastructure for streamed data that enhance contemporary generative and large
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intelligence and machine learning across several domains of physics and astronomy. The successful candidates will develop an integrated image-processing pipeline and apply it to three distinct problems: rare
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Weather and climate prediction are undergoing a profound transformation. Alongside traditional physics-based forecast systems, machine-learned (ML) weather prediction models, hybrid ML-physics
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evolution. ● Experience with population genetics. ● Experience developing R packages. ● Experience applying or developing machine learning tools. ● Strong scientific writing skills. Brief
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and meteorological modeling. Experience running or maintaining operational/automated forecast systems. Experience applying machine learning methods to air quality or geophysical data (e.g., forecast
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architecture of entirely new foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across