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% of your total appointment, averaged over the course of your PhD. Job requirements Essential An MSc degree in systems & control, electrical engineering, mechanical engineering, applied mathematics, physics
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motivated candidate, with a keen interest in plankton trait-based ecology and ecosystem modelling. You enjoy process-based ecosystem modelling, are well-organized, have a collaborative personality but are
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Engineering, Electrical Engineering, Medical Imaging, Applied Physics, Computer Science, or a related field. Strong affinity with ultrasound imaging, signal processing, medical image analysis, or computational
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? The NWA-ORC funded consortium project ABEL addresses this challenge by combining technology development with process modelling and assessment across the waste value chain. The members of the consortium
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with colleagues. Selection process The application should include the following documents: • Curriculum vitae • Research statement or working paper • Transcript of all university grades • (recommended
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should be prepared in English and sent merged as ONE pdf file. Selection process The decision will be made by the Scholarship Committee established by the Vice-Rector of the University of Gdańsk and
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-of-concept of smart health systems. Requirements for candidates: Essential: BSc and MSc in biomedical engineering, engineering, physics, biomedicine, or a related field. Master thesis in biomedical engineering
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develops LLMs and agentic AI systems for scientific discovery, engineering and physical systems. We investigate how AI can reason about scientific problems, interact with simulation software and support the
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 3 months ago
parametric studies following a design of experiments and to generate databases of physical fields that can be used to train generic meta-models [McCabe et al., 2025]. Furthermore, since industrial equipment is
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methods that extend current sets of flood scenarios derived from physical and numerical models, incorporate climate change effects, and then use these enriched datasets to assess the future insurability of