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Field
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machine learning, deep learning, or data assimilation. Experience with scientific programming (Python, R, MATLAB, etc.) and geospatial tools (ArcGIS, QGIS, GDAL, GeoPandas, etc.). Demonstrated publication
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signal-to noise Post-processing: denoising, reconstruction algorithms Comparison with high-field MRI: deep-learning and other AI modalities for low-field MRI optimization Close cooperation with
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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/C++, FORTRAN and/or Python. Experience working with geo-spatial information, remote sensing data, and GIS software. Experience in deep learning and computer vision. Experience in developing software
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, Greninger Lab Position Details Position Description The Greninger Lab at the University of Washington is seeking a Postdoctoral Scholar driven by curiosity, eager to dive deep, think big, and learn fast - a
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of faculty at SUNY Polytechnic Institute and the University of South Florida, consisting of mathematicians, physicists, computer scientists, and engineers investigating applications of deep learning
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controls, using deep learning and explainable AI Communicate and discuss results with stakeholders to integrate the findings into water management practices Interpret, publish and present findings in peer
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experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer architectures, attention mechanisms, and fine tuning techniques for LLMs. Experience with time
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Computer Science, on topics related to Artificial Intelligence and Machine Learning, Human-Robot Interaction and 3D Vision/Multimedia. Experience with deep neural models and algorithms for 3D spatial reasoning and
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, and MRV performance) and identify optimal deployment models coupled with learnings from forest management. Conduct techno-economic and life-cycle assessments (TEA/LCA) integrating forest operations