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Field
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validated predictive models of pavement deterioration. The position is research-focused, with opportunities to strengthen independence and build qualifications for future academic or industry careers
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PhD and MSc students working on related topics. This position offers an excellent opportunity to advance expertise in a rapidly evolving field, while also gaining experience in managing research
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checks. Both parts are meant to support data-driven computational modeling for applications in epidemics. For a further description of the proposed project, see this document. The Department
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, with a PhD in the field of economics, (business) mathematics, (business) informatics, marketing, management; Experience in data analysis, statistical and econometric modeling; Good skills in writing
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, as well as: A PhD degree in the field of renewable energy engineering (or close to obtaining one), or in a closely related field. Demonstrable experience in Python and relevant modelling tools, like
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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to apply and develop cutting-edge deep generative probabilistic models
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, in coordination with PI, that investigates the governance of new funding models for creators and influencers, collect and analyse empirical data (flexible, but please specify), present research
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the Oxford–Novartis Collaboration for AI in Medicine. You must hold a PhD/DPhil in Statistics, Statistical Machine Learning, Deep Generative Modelling, or a closely related field, together with relevant
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Max Planck Institute for Extraterrestrial Physics, Garching | Garching an der Alz, Bayern | Germany | 5 days ago
. The start date of the position is October 2026, with some flexibility (to be negotiated). The position is limited to three years and according to current German labor law. Applicants must have obtained a PhD
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to differentiate between healthy and accelerated brain aging; ii) create multiphysical constitutive models of cortical tissues degeneration during aging and injury; iii) utilize longitudinal medical image data