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, and/or numerical mathematics, as well as an excellent command of a programming language, preferably Python or C/C++. The candidate should have an interest in modeling and solving a complex, coupled
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Python or C/C++. The candidate should have an interest in developing novel bivariate methods in machine learning for molecular property prediction within an interdisciplinary application. Ideally
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degree in bioinformatics, computational biology, statistics, or a comparable field Strong programming skills in common analysis environments such as R and/or Python Experience in the analysis of single
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systems and basic knowledge in information theory ▪ Proficiency in at least one programming language (e.g. Python) ▪ Interest in AI‑based attack models and security research The following points
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skills. Experience with programming, preferably Python and R, is required. Experience with deep learning frameworks, such as JAX or PyTorch, is a plus. In addition to above-average interest in the topic
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skills. Experience with programming, preferably Python and R, is required. Experience with mass spectrometry data, in particular metabolomics, and geometric machine learning is a plus. In addition to above
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a related field ▪ Strong knowledge in wireless communication systems, signal processing, or radar systems ▪ Proficiency in at least one programming language (e.g. Python) ▪ Interest in hands
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research group (please find further information at https://www.biologie.uni-konstanz.de/gruber ). You will be developing machine learning-based data science approaches for the analysis of Next Generation
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(https://www.cliccs.uni-hamburg.de/about-cliccs/cliccs-ll.html ). In CLICCS-M4, we are further developing the unique ICON-Coast model within the ICON Earth System Modelling Framework. The objective
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allowance. The employment will initially be limited to three years. Important: Applicants must not have resided in Germany for more than 12 months in the past three years. Group website: https://biophys.uni