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collaboration in optimising data analysis algorithms for the raw detector data, including improving position reconstruction and pulse-shape discrimination algorithms which can be implemented on in the front-end
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functional data ”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines for plausible narratives of regional climate change, novel algorithms for rare
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for plausible narratives of regional climate change, novel algorithms for rare event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components
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with immigrant backgrounds and people with disabilities are encouraged to apply for the position. We encourage women to apply. If multiple applicants have approximately equivalent qualifications
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employees is therefore a goal. People with immigrant backgrounds and people with disabilities are encouraged to apply for the position. We encourage women to apply. If multiple applicants have approximately
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://www.lcbc.uio.no. Job description Develop quantitative models to estimate how the brain and various cognitive processes change throughout life. Process and analyze data from multiple sources, including behavioral
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Experience in working with deadlines and being involved in multiple projects We offer A full-time contract for two years with possibility for extension, depending on the availability of funding. A 6 months
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difficult to identify the contribution of the applicant in multiple-author publications, a short explanation about the applicant’s part of the work is suggested. Applicants invited for an interview will be