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illumination variations, which introduce non-stationary shifts and degrade the performance of conventional models. The project proposes the use of hypernetworks to dynamically adapt the parameters of the gaze
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, designing, implementing, and evaluating ML models that address practical challenges across domains. The researcher will contribute to the development of a full machine learning pipeline, including data
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preparation and testing or powder mixtures, and then to devise predictive models (possible using machine learning approaches) for the estimation of mixture properties from pure component propeties. The PhD
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this early phase of settlement, particularly the routes taken. Main tasks: - Conduct demographic modeling analyses based on human genomic data. - Write a manuscript based on the results of the analyses
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also connected to the Wallenberg Initiative Materials Science for Sustainability (WISE, https://wise-materials.org ). WISE, funded by the Knut and Alice Wallenberg Foundation, is the largest-ever
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research tasks: (i) modeling electric and magnetic excitations in two-dimensional (2D) materials, and (ii) simulation of charge transport phenomena in plasmonic crystals with 2D electron gas layers, with
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research tasks: (i) modeling electric and magnetic excitations in two-dimensional (2D) materials, and (ii) simulation of charge transport phenomena in plasmonic crystals with 2D electron gas layers, with
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the EU’s ambitious AI Factories initiative. Learn more: https://mimer-ai.eu/about-mimer/ , https://www.naiss.se , https://eurohpc-ju.europa.eu/ai-factories_en The position In this role your responsibility is
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future change), which utilises the geological record of glacial change during the last glacial-interglacial transition to isolate seasonal climate parameters needed for modelling future climate. The
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have become a major challenge for understanding, recording, and modulating neuronal network activity, ranging from in vitro cellular models to implantable neurotechnological applications. In the long