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technologies. Collaboration with national and international research partners. Guidance and support from experienced supervisors and fellow researchers. Application procedure For more information please contact
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many real-world applications, finding a solution requires high-performance computer clusters that consume large amounts of energy and run for a long time. Our project aims to create a radically new
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the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning
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catalysts. Particular attention will be given to investigating structure-function relationships during different stages of the CO₂-to-alcohol cascade process. TEM data will help clarify the spatial
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, for the preparation of a doctorate, contains: We invite you to apply for a PhD position supported by the Marie Skłodowska-Curie Doctoral Network HARNESS - Harnessing AI and Data-Intensive Technologies
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to teaching activities (1-2 course hours per week or equivalent through student supervision) For further information please contact Prof. Frank Scholzen ( ) Your profile A Master's degree in Engineering (Energy
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devices. The project will involve significant collaboration, sample exchange, semiconductor and device characterisation. For more information on the position please contact Prof. Phil Dale or Prof. Alex
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. Karel Neels (Department of Sociology, University of Antwerp) and principal investigators Sylvie Gadeyne (VUB, BRISPO, Interface Demography )) and prof. Niel Hens ( University Hasselt, Data Science
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Schoonjans (Pediatric Neurology Department UZA) are seeking a highly motivated PhD student to work on clinical data analyses and multi-omics approaches in the rare genetic neurodevelopmental syndrome, STXBP1
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(bio-)chemistry, physics, and engineering expertise to study molecules and cells, taking advantage of optical and single-molecule imaging, molecular probes, molecular biology, and 'large' data analysis