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to funder reporting Qualifications · Must have a PhD or equivalent in applied mathematics, statistics, biophysics, or similar. · Must be able to undertake full-time research and scholarship. · Must be able
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conferences. support the teaching activities at the faculty (up to 10% of the time). What we ask of you A PhD in Machine Learning, Computer Science, Mathematics, Statistics, Physics or a closely related field
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a modeling approach inspired by statistical physics to describe individual strategies, their interactions, and emergent effects at the group scale. The candidate will contribute to the development and
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closely related field PhD training covering topics such as computational modelling, numerical methods, statistical analysis, machine learning or data-driven analysis of complex systems Experience 0–3 years
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completing a PhD in a subject relevant to the project, which includes (but is not restricted to) statistical physics, biological physics, soft condensed matter physics, and fluid mechanics. The post is funded
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will be working in an experimental lab, performing data collection, analysis, and modeling of behavioral and electrophysiological data. Applications are invited to apply for a statistical data analysis
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patterns, and alternative integrated and humanized approaches to public security. Requirements: • Completed PhD in any field; • Knowledge of advanced statistics and at least one programming language (R
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and pursue independent research directions. Required Qualifications: Completed PhD in Statistics, Biostatistics, Computer Science, Bioinformatics, or a closely related area prior to their appointment
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Biological sciences » Biodiversity Biological sciences » Biology Chemistry » Computational chemistry Technology » Biotechnology Physics » Mathematical physics Physics » Statistical physics Physics » Biophysics
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invite applications for a postdoctoral position in the group of Axel Ringh at the Division of Applied Mathematics and Statistics, Department of Mathematical Sciences, with focus on computational methods