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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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can be tackled. A video describing the project can be viewed here: https://www.youtube.com/watch?v=IzPuuBnrIDc . The successful candidate will be developing Bayesian models for estimating
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includes excellent healthcare, retirement plans, tuition assistance, paid time off, and a winter recess. POSITION OBJECTIVE Working under general supervision, the Advanced Data Analytics Research Analyst
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statistical shape analysis, Riemannian geometry, time series and stochastic processes, and Bayesian statistics. Key responsibilities: To carry out research within the framework of the project, under
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for employment on a part-time or other flexible working basis, even where a position is advertised as full-time, unless there are operational or other objective reasons why it is not possible to do so. 18 months
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part of the EU-funded project IM4CA (https://im4ca.eu). Work duties The PhD student will carry out research related to the objectives of IM4CA. In particular, this project will employ a wetland CH4
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statistical shape analysis, Riemannian geometry, time series and stochastic processes, and Bayesian statistics. Key responsibilities: To carry out research within the framework of the project, under
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”, 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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candidate will collaborate with investigators within and outside Duke University. The objectives of the projects are: to identify and validate surrogate endpoints of overall survival using data from cancer
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research and soft robotics development. PhD project The PhD project will focus on the technical aspects of simulating the physics of the Drosophila larva body. The primary objectives include: Developing a