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AI-Based Forecasting Models We invite applications for a PhD position focused on developing next-generation AI-based forecasting models to enhance renewable energy (RES) integration into power systems
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. The post holder will work with the Bakshi Lab's single-cell phage infection platform (https://www.bakshilab.net/ ) and an interdisciplinary team spanning microbiology, engineering and quantitative
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model of magmatic oceans on forming planets based on laboratory experiments. At present, high-pressure molten silicates are modelled only in a rudimentary manner, due to a lack of data on activity
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. Subsequently, a secondary atmosphere would have been degassed or brought in by a late veneer of chondritic/cometary material. Although this model is regularly evoked using giant planets for comparison, there is
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for an interview. In order to be considered as an applicant in these groups, the applicants must meet certain requirements. You can read more on this here: https://arbeidsgiver.difi.no/positivsaerbehandling . We
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of Marine Technology at NTNU has a vacancy for a PhD Candidate in Deep Learning enhanced FSI modelling of Multi-modular Floating Structures. The position is part of the AIMOS project (Artificial Intelligence
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 1 month ago
Science (MarDATA). MarDATA’s interdisciplinary focus spans supercomputing, modelling, (bio)informatics, robotics, statistics, and big data methodologies. Doctoral researchers benefit from a structured
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, you will have the opportunity to advance scientific expertise on integrated modelling of the entire water cycle, with particular focus on real-time simulations and operational forecasting. A key element
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» Modelling tools Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 15 Sep 2026 - 00:00 (Pacific/Saipan) Country Germany Type of Contract Temporary Job Status Full-time
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authenticity of visual media and provide understandable evidence for model decisions. The candidate will investigate how general-purpose pretrained visual and multimodal representations can be adapted