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production of bacteria via mass spectrometry Statistical analysis of the resulting data The successful candidate will have the opportunity to work towards a PhD Required qualifications: University degree (M.Sc
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Description 3 x Academic Researcher (m/f/d) (TV-L E 13, 100%, Service Location: Clausthal-Zellerfeld) The research group Dependable and Autonomous Cyber-physical Systems (DACS) at the Institute
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security, health insurance, and other statutory costs will be deducted in accordance with the applicable national regulations. Covered tuition costs, research costs and funding for short term mobility (i.e
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eligible, a family allowance. The stated allowances represent the gross funding amounts. Employer contributions to social security, health insurance, and other statutory costs will be deducted in accordance
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. The stated allowances represent the gross funding amounts. Employer contributions to social security, health insurance, and other statutory costs will be deducted in accordance with the applicable
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experience with methods of molecular biology and/or in the field of histology Experience in animal experimentation is an advantage Knowledge of statistical methods for data analysis Very good written and
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performance, detect artefacts, and ensure scientific rigor Proficiency in Python (or Julia/R) for data handling, ML model development, and statistical analysis Ready to work with time‑series data, sensor fusion
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for the efficient analysis of the experimental data. For more information, visit our web page www.soft-matter.uni-tuebingen.de We are looking for a motivated PhD student to contribute to the studies of protein
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, artificial intelligence, and security, with a focus on tools and techniques for constructing reliable, efficient, and secure software. General areas of research include: Artificial intelligence to reason about
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and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team