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studies within the Marie Skłodowska-Curie Actions (MSCA ) funded network program for PhD students, IDEAL4GREEN , that addresses the urgent challenges of climate change and the global shift towards
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for large-scale simulations of cortical memory function. Special focus is on coupling multiple neural networks to study neural interactions between different cortical regions supporting cognitive function
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visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between PhD-students, researchers and
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control strategies that strengthen their disturbance-handling capability. The work will be carried out with in a MSCA-DN doctoral training network with research stays at DNV in the Netherlands, Aalborg
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. The research team focuses on developing novel methods to extract knowledge from data, modeling large-scale complex systems, and exploring new application areas in data science. Areas of interest include but
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advanced methods in AI and machine learning, combined with atomistic spin dynamics and first-principles electronic structure calculations, to study complex nanomagnetism. A specific goal of the project is to
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(CFD) of new solutions for capturing biogenic CO2 from point sources. The work will consist in creating simulations tools based on CFD to simulate details on CO2 capture by solvents in complex geometries
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Gionis. The position is part of the European project ARMADA funded by the Marie-Skłodowska-Curie Doctoral Network. The ARMADA project operates within the fast-growing field of Conversational AI, aiming
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for clean, abundant energy, and the binding targets to reach net-zero emissions by 2050 are among the driving forces for this renaissance of nuclear power. After a long period with no new deployments in
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(ISAC), massive and distributed MIMO at sub-terahertz frequencies, and terahertz communications for satellite networks. The research will focus on the physical layer and media access control layer