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Field
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Master's degree in Mathematics, Statistics, Operations Research, Industrial Engineering, Computer Science, Data Science or a related field Strong mathematical and analytical skills for model formulation
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Condensed Matter , Theory , topological states Quantum Computing Condensed Matter and Statistical Physics / Dynamical and non-equilibrium phase transitions Quantum Optics / Ultracold Atomic Gases Quantum
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active learning is desirable, as well as knowledge of behavioral coding programs (e.g., Datavyu) and mastering of statistical methods and programming languages (e.g., R, Python). Experience with online
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, Human-Computer Interaction, and their responsible applications. Ideal candidates will have: An M.Sc. degree (or equivalent) in Computer Science, Game Engineering, Mathematics, Statistics, or related
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or natural sciences Sound knowledge in machine learning algorithms, statistical methodologies, and biological network analysis Experience with the analysis and integration of transcriptomic and multiomics data
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, computational data analysis and microbial evolution, with a solid understanding of quantitative statistics and programming (Python, R, MATLAB, etc.). Additional expertise in ancient DNA, (bio)archaeology
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, TensorFlow, Pandas), ideally combined with knowledge of data visualization or statistical analysis Knowledge of software development (e.g., Python, Matlab, Simapro), especially in combination with experience
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statistical expertise and mentorship to PhD candidates within the LEVER project. Support the research activities of the Cultures of Sustainability Unit. Assist in the development and delivery of teaching and
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candidate (m/f/d) has expertise in population genetics, computational data analysis and microbial evolution, with a solid understanding of quantitative statistics and programming (python, R, matlab etc
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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | 2 months ago
related field. Experience with time series data analysis (e.g., EEG, physiological signals, behavioral data), ideally combined with a solid background in statistics. Interest in or familiarity with