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Willingness to familiarise yourself in depth with new topics in the fringe area between algorithm development, high-performance computing and experiment Good problem-solving skills Willingness to work in teams
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the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD
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degree at a German university Duration of the funding Approx. 2 years depending on the duration of the Master's programme Value Co-funded by COLFUTURO and DAAD Intensive German course in Germany (up to 6
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PhD project involves interdisciplinary research at the interface of computer science and mathematics and addresses a complex, coupled inverse problem with explicit uncertainty quantification. Research
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are among others: above average academic performance personal suitability for the programme and its objectives knowledge of the German language (at least level B1) good command of English The selection
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to you on the website: https://tu-dresden.de/karriere/datenschutzhinweis . This project has received funding from the European Union’s Horizon Europe research and innovation program under the MARIE
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this with expertise in high‑performance computing and artificial intelligence using unique scientific infrastructures. At the Institute of Energy Technologies – Fundamental Electrochemistry (IET‑1), we
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60% of the coursework in their degree program. What can be funded? A study semester at a German university, followed by a 4 to 6 month internship in a German company Duration of the funding 12 months
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international work environment Scientific excellence and extensive professional networking opportunities A structured PhD program with a comprehensive range of continuing education and networking opportunities
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the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD