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Master’s degree (or equivalent) in mathematics, computer science, physics, or related field. Sound knowledge in (scientific) machine learning, and knowledge in numerical analysis and numerical linear algebra
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(at least finished before July 2025) very good programming skills and AI/ML knowledge good written and spoken English skills (CEFR level C1 or higher) We offer: cutting-edge research in data science and
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HPC environments Good communication skills to interact with collaborators ranging from machine learning researchers to pathologists or medical students Knowledge of biology and medicine is a plus Highly
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knowledge gap exists regarding their impacts on microorganisms in the environment (Zabaloy et al., 2022). Previous studies show mixed results on the effects of surfactants on glyphosate biodegradation
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profound knowledge in computational and theoretical physics/chemistry. Capability of team work is essential. Skills in high-performance computing, materials chemistry, theoretical chemistry, molecular
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, Radioecology, Mineralogy, Geology or related field Experience in experimental and analytical work and in the evaluation of extensive analytical data sets Knowledge of handling radioactive substances is desirable
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) and should be used for a doctorate. Participation in the accompanying doctoral program is compulsory. This serves to impart both scientific and methodological knowledge and offers the opportunity
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Completed university studies (Master/Diploma) in the field of Chemistry, Radiochemistry, Radiopharmacy, Radioecology or related field Excellent knowledge of a broad range of organic chemistry and analytical
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atomistic simulations, high-performance computing, and the application of AI-based methods Basic knowledge in photovoltaics and solid-state materials for energy application Ability to work individually and in
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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did