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Field
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, machine learning, deep learning, high powered computing (requiring Python etc) or a combination of data science and qualitative methods (e.g., interviews and focus groups). Project themes include (but
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to plant biosciences where the impact could be huge and as a result exciting opportunities get missed. When we use light to image deep into complex samples there is a common problem that occurs – the light
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, computer science, computer vision, machine learning, state estimation, perception, sensor fusion, autonomous systems, navigation and control Deep foundation in modern machine learning Solid programming skills in C
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. Additional qualifications Experience with one or more of the following areas is meriting: Bayesian statistics, mathematical modelling, probabilistic machine learning, deep learning, large language models
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Initiatives in Forest Research (WIFORCE) program. The successful applicant will work on the development of bioacoustic monitoring methods using automated recording units (ARUs), deep learning methods, and
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control Deep foundation in modern machine learning Solid programming skills in C++ and Python. Experience with ROS is a plus Extensive hands-on/practical experience on developing, implementing and/or
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | 3 months ago
expose the successful candidate to cutting-edge genome editor engineering approaches and the delivery of these reagents in vivo via AAV or lipid nanoparticles. The successful candidate will also learn
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++ or similar) and an interest in quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not
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approach based on Deep Learning algorithms will be developed and implemented to obtain additional information by coupling the recorded data. Furthermore, the increase in acquisition rates of measurement
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Functions Developing and implementing machine learning and deep learning models to analyze forestry, physiological, and ecological datasets Modeling plant growth, carbon allocation, stress response (e.g