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physics, as well as the team’s work on applied mathematics and advanced numerics, via the ACT website ( https://www.esa.int/gsp/ACT/) . You also are encouraged to visit the ESA website: https
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plant growth, physiology and disease development; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning
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European Magnetism Association EMA | Nijmegen, Provincie Gelderland | Netherlands | about 2 months ago
Home > JOBS Ultrafast Magnetism in Frustrated Materials [ All offers ] 2026-07-24 | PhD Lab/Company : HFML-FELIX Location : Nijmegen, Netherlands Yearly income : https://www.nwo-i.nl/en/vacancies/phd
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, and bring together technology and service providers, customers, researchers, investors and institutional partners. You can read more about BSGN on the website: https://bsgn.esa.int You are
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characterize subsurface structures, buried infrastructure, and material properties; · develop and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction
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make these environments observable. You will design and validate a cost-effective, synchronised multi-node sensing system for simultaneous time-domain measurements of voltages, currents, electric
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affinity for language data; solid programming skills (e.g., Python) and experience with machine learning or NLP, ideally including transformer-based models and word embeddings; excellent English
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Eindhoven University of Technology (TU/e) | Eindhoven, Provincie Noord-Brabant | Netherlands | 2 months ago
high demand. You will be supervised by Dr Gabriele Liga ( https://www.tue.nl/en/research/researchers/gabriele-liga ) and Dr Yunus Can Gültekin at TU/e. You will carry out two research secondments: one
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MSc related to geoinformation science and earth observation, spatial and spatiotemporal modelling, spatial statistics, and/or machine learning. You enjoy applying these modelling skills to analyse and
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statistics group is on the development of statistical methodology for new data applications and the theoretical analysis of machine learning methods. A list of members of the statistics group can be found