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machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates will have the opportunity to collaborate closely
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with health/real grid data or machine learning is beneficial but not mandatory. We Offer One year funded of 3-year PhD position (SIF Doctoral Student Grant). Access to high-performance computing
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school, and taking part in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, scientific computing, statistics, physics or a
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Excellent English proficiency, spoken and written IT user skills (computer literacy) Ability to work in a team Desirable: Good knowledge and solid understanding of language learning and teaching research with
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, personal and parental leave, Employee Assistance Program, Medical Hub on Campus, Novated Car Leasing, 25% discount on some short courses, personal software discounts, among others About the position The VE
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doctoral degree Collect, structure and assess relevant sensor, operational, maintenance, incident and cost data Develop and validate statistical, causal and/or machine-learning methods and turn the results
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will focus on efficient probabilistic analysis of high-dimensional and dynamic systems, including advanced sampling, surrogate modelling, and AI or machine-learning methods where appropriate. Key
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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of Computer Science at McGill University (Montreal, Canada) invites applications for tenure-track appointments at the rank of Assistant Professor. We are seeking candidates with a PhD (or close to finishing) and
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initiatives. OR Doctoral degree in a quantitative discipline with demonstrated expertise in statistical modeling, machine learning, data science, research methodology, or related analytical fields. Required