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the complex multiscale nonlinear interactions at the origin of such extreme events. In this project, you will develop machine learning-based reduced-order models which can accurately forecast
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? No Offer Description 1 (one) Research Fellowship under Special Regime (BI-RE) for a PhD Student 1 Research Fellowship(s) under Special Regime (BI-RE) is(are) open at the FCiências.ID – Associação para
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a PhD stipend in the field of Real-time stream data analysis within the general study
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transcriptomics and multi‑omics data. You will also partner with AI experts to integrate predictive models and advanced analytics into omics workflows. You will work in an expanding team led by Dr. Masoomeh
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science » Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 May 2026 - 23:59 (Europe/Madrid) Country Spain Type of Contract Temporary Job Status Full-time Hours Per
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structured around a dual theoretical and experimental component: the PhD student will be required to model the physical phenomena involved in the measurement, as well as to design and develop new experimental
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focus on performing analysis of the data and computational modelling of neuro-circuits. The project will be carried out with Professor Daniele Faccio at the Advanced Research Centre, University of
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for personal and professional development with support from experienced PIs. FLEXIBILITY: Flexible working time models, including options close to full-time ( https://go.fzj.de/near-full-time ), allow you to
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First Stage Researcher (R1) Positions PhD Positions Application Deadline 29 Apr 2026 - 15:00 (Atlantic/Reykjavik) Country Iceland Type of Contract Temporary Job Status Full-time Is the job funded through
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months ago
Europe Research and Innovation Programme under the Grant Agreement No.101178775 Workplan: Design, develop and implement deep learning methodologies for generation of subsurface earth models. Duration