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following position Postdoctoral researcher (m/f/d) in Environmental Data Science and Machine Learning for the project BoTiKI Location: Görlitz Employment scope: full-time (40 weekly working hours) / part
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The Network Analysis and Modelling group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using machine learning and network
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or a related discipline A solid background in climate and atmospheric sciences, and extreme weather ideally supported by knowledge of machine learning and time series analysis is of advantage, as is
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omics, environmental, and chemical data, using machine learning and explainable AI. Depending on your background, interests, and evolving project needs, your work may focus on one of these areas or bridge
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or Python Machine learning methods (for the baseline prediction for the reward funds) is beneficial We expect: Strong motivation to contribute to policy-relevant research Strong interest in teamwork and
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-processing, and machine learning textual analysis of the full text of policy documents. Qualitative content thematic analysis is envisioned to compliment structural topic modelling to identify strategies and
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, survey) or applied microeconometrics, and applied economics. You have experience with big data and machine learning methods? This would be a particular asset! With excellent English language skills, both
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learning settings with a specific focus on museums. The lab uses a variety of methods (e.g. eye-tracking, VR) covering the entire continuum from computer-based tasks to real-life engagement. With the aim
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-processing, and machine learning textual analysis of the full text of policy documents. Qualitative content thematic analysis is envisioned to compliment structural topic modelling to identify strategies and