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Description As part of the German government's artificial intelligence (AI) strategy, the successful Saxon competence center ScaDS.AI Dresden/Leipzig (Center for Scalable Data Analytics and
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-specific and inter-specific interactions, give rise to a complex macroscopic behavior. They are described by nonlinear systems, which pose many analytical challenges. Tasks: scientific research
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both experimental and conceptual work, be eager to learn, and value teamwork. Experience with bioreactors, analytical instruments, and microbial cultivation is a plus. Good communication skills and
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. Qualifications The applicants should possess: an excellent or very-good university degree in economics, business studies, agricultural sciences with a focus in economics, or related disciplines strong analytical
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machine‑learning or data‑analytics tools High‑level programming skills (Python, R, Julia) to build, test, and optimize models of geochemical systems Interest in large‑scale computational simulations (e.g
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, agricultural sciences with a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
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complex materials with tailored properties using high-throughput simulations, data analytics, and material characterization. Benefit from strong connections to top research infrastructures like the Jülich
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, excellent quantitative analytical and statistical as well as communication skills are required. Working enviroment Apart from working closely with colleagues at the Kiel Institute and within the Leibniz
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analytical programming language (e.g., Python, R) or a universal programming language (e.g., C#, Java, C++, Rust) Knowledge of the use of relational and non-relational databases Very good English skills