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RTG3120 on Biomolecular Condensates ( https://dresdencondensates.org ). Each PhD project is part of an interdisciplinary framework that includes shared training activities, and supervision by
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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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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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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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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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English to derive the full benefit from the network training as secondments and events are foreseen, applicants must be ready to travel Applicants must be eligible to enroll on a PhD program at TU Dresden
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C++ or MATLAB are an advantage) Experience with Linux-based computing systems and computing clusters is desirable Interest in interdisciplinary research at the interface of physics, data science, and
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Mobility (IAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in highly automated, networked mobility, featuring
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candidate will be embedded in the DFG Research Program RTG3120 on Biomolecular Condensates ( https://dresdencondensates.org ). Each PhD project is part of an interdisciplinary framework that includes shared
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of the host organization of last 36 months. As secondments and events are foreseen, applicants must be ready to travel Applicants must be eligible to enroll on a PhD program at TU Dresden (see https://tu