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engineering, or a related field. · Strong background in machine learning or data analytics and hands-on experience handling big data. · At least one year of research experience in transportation
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well as bulk RNA-Seq, Proteomics, and Metabolomics generated from mouse and patient cohorts with rich clinical data - Advanced modeling of arrhythmias using generalized linear models and machine learning
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or experience in nontraditional research publication methods and collaborative notetaking software (e.g., Roam Research, Obsidian, Notion). ? Familiarity with cloud computing and machine learning techniques
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Pneumatic Tires, Structure-Process-Properties Relationships. As part of it, we are currently looking for a postdoc on machine learning for road characterization. How will you contribute? Do you have proven
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R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working
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Postdoc in modelling Greenland and Himalaya precipitation using machine learning Faculty: Faculty of Science Department: Department of Physics Hours per week: 36 to 40 Application deadline: 26
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of efficient and robust neural networks. About your role: Independent research in the area of mathematics of machine learning, focusing on the development as well as the analysis of different algorithms and
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assimilation and machine-learning techniques, (b) process understanding of the neighborhood risk of heat waves and fires associated with the change of weather pattern, and (c) novel algorithm development
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biogeochemical model using times series forecasting and machine learning. The Post Doc will focus on one or two of the questions depending on their expertise and interest. Minimum Acceptable Education & Experience
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Scholar appointments to a total of five years, including postdoctoral experience(s) at other institutions. The University of Washington and the International Union, Automobile, Aerospace and Agricultural