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local gas/liquid phase conditions. Whilst direct simulations of breakup are possible, computational cost is high, restricting applications to small sections of geometry and for modest run times
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: A completed university degree (Master’s or equivalent) with excellent grades in computer science, materials science, physics, or a related discipline Practical experience in data science, including
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. The PhD study must be completed in accordance with The Ministerial Order on the PhD programme (2013) and the Faculty’s rules on achieving the degree. Salary, pension and terms of employment are in
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computing. Current challenges in quantum technology adoption stem from the lack of standardized benchmarking methods and the inherent difficulty in validating quantum devices beyond classical simulation
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culturing, etc.) Strong interest in phage biology & antimicrobial resistance Preferred: Experience with omics data analysis (esp. RNA-seq, proteomics) Bioinformatics tools and computational skills (R/Python
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state-of-the-art high heat flux testing, simulating the extreme environments of fusion reactors. Harness advanced computational tools to model complex particle-material interactions and predict material
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) with excellent grades in computer science, materials science, physics, or a related discipline Practical experience in data science, including the application of machine learning (ML) methods or large
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-free double perovskites Your Profile: Master`s degree in theoretical or computational physics, chemistry, materials science or similar fields Familiarity with atomistic simulations, high-performance
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novel computational imaging and sensing techniques for compact imaging systems. These systems are applicable to all sectors which require compact imaging specifications, but will have a primary focus on
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the EU Research Framework Programme? Horizon Europe - MSCA Reference Number DC1 Marie Curie Grant Agreement Number 101225914 Is the Job related to staff position within a Research Infrastructure? No Offer