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). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing provably powerful learning models for graphs will
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Network: ENDOTRAIN (Digital Endocrinology Training Network to Combat Adrenal Diseases) , and is scheduled to start in August 2026. The position is funded by European Union’s Horizon Europe research and
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evolutionary procesess have shaped the organization of human cognitive brain networks and their cognitive functions and vulnerability to mental conditions. By applying neuroimaging, genetics and network
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part of the project, and hence skills in computations and implementation (via codes written in open source software, such as R, Python, ...) are a plus. A good knowledge of written and spoken English is
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To combat climate change and achieve the UK's target of Net Zero, it is expected that the integration of renewable energy sources (RESs) at the distribution/consumption level will keep increasing
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Inria, the French national research institute for the digital sciences | Toulouse, Midi Pyrenees | France | 21 days ago
be conveniently adapted, not only by local mesh modification (h-adaptive), but also by locally varying the degree p of the polynomial reconstruction. Local p-adaptation can reduce dissipation and
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The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences | Poland | 1 day ago
position, fixed-term contract of 4 years for the full duration of the doctoral programme, - Remuneration/month: 5.500 PLN net/month, - The position starts on the 1st of Feb 2026, - Work in an active team in
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months after completed the PhD-degree, if this is achieved within a shorter time than three years. The position is part of the Doctoral Network: ENDOTRAIN (Digital Endocrinology Training Network to Combat
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PhD Studentship - Process Industries: Net Zero - Optimisation bio-methanol production from high-moisture feedstock Award Summary 100% fees (UK Home only), a minimum tax-free annual living allowance
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both challenges and opportunities for achieving net‐zero carbon targets. While AI data centres are often perceived as passive electricity consumers, they could act as active participants in integrated