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Postdoctoral Researcher in Citizen Science & Societal Engagement for an Inclusive Energy Transition,
entails, please contact Antonella Maiello Assistant Professor Governance of Sustainability, at a.maiello@fgga.leidenuniv.nl . You can apply until 25 August 2025. Shortlisted candidates will be interviewed
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; developing visualisation prototypes to communicate uncertainty to end-users; contributing to a computational framework for data production in cooperation with Research Software Engineers; working closely with
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. Hendriks (Jan) Professor - Environmental Science jan.hendriks@ru.nl Last modified: 08 August 2025 Share this page Facebook WhatsApp Mastodon Twitter LinkedIn E-mail
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represent interests of ESA and of the upcoming sample curation community, including organising and chairing meetings and working groups and coordinating community activities associated with sample curation
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learning and data augmentation for soil and biomass carbon forecasts; developing a computational framework for data production in cooperation with Research Software Engineers; collaborating and coordinating
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researcher with expertise in the area of spiking neural networks and an interest in (applications of) probabilistic computing. The postdoc candidate will participate in the NWO NWA project "Acting under
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by the Netherlands Organisation for Scientific Research (NWO) programme GroenvermogenNL. In Europe, the Netherlands ranks as the second-largest hydrogen producer. As it stands, the vast majority
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Division, Systems Department, Directorate of Technology, Engineering and Quality. The Future Engineering Division, in support of the programme directorates, is responsible for developing and providing
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mission. supporting the yearly/bi-yearly maintenance of the mission classification PA requirements and the associated PA requirements document templates for each class of mission. supporting, when feasible
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August 2025 Apply now Machine Learning models are increasingly important in the atmospheric sciences. After training, they can emulate model outcomes at a fraction of the computational cost of traditional