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Field
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events. Maintain and perform analysis on large quantitative datasets; develop and implement statistical or machine learning models to recover patterns of technology adoption, task organization and skill
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, or demonstrate a willingness to acquire relevant expertise rapidly. Proficiency in coding, numerical modeling, and experience with periodic DFT codes or MOLCAS are desirable attributes. The start date
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imaging, computer vision, and predictive modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring
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Finnish Sign Language. The responsibilities of the appointee include developing approaches that use automatic speech recognition, computer vision models and other computational methods to annotate the data
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. · Strong background in machine learning/AI and hands-on experience with large, heterogeneous datasets. · Practical experience with computer vision and/or spatio-temporal modeling (object detection
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) with questions related to this position. Major Duties/Responsibilities: Develop and apply machine learning models (ML) as surrogates for high-resolution process-based hydrologic models. Design and
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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tools in research. Excellent written and oral communication skills, with a proven track record of publishing scientific papers and delivering presentations. Experience with machine learning techniques
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provides a unique opportunity to work at the interface of plant genomics, metagenome analysis, and computational systems biology, in collaboration with researchers at national laboratories (PNNL, NREL) and
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that you are eligible for, including health insurance, retirement plans, and paid time off. To access this tool and learn more about the total value of your benefits, please click on the following link