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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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-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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scales. The scientific evidence-based knowledge developed in ISOLUME will be used to develop a roadmap for implementing changing marine lightscapes as an indicator in management policies, monitoring
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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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Family-friendly working conditions (certificate “audit berufundfamilie”) Supporting of mobility with a jobticket for using the public transport Easy accessibility by public transport or car (including free
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policies, monitoring programmes and essential ocean (biodiversity) variables. ISOLUME is a collaborative effort between IOW and 10 European partners and is supported by the JPI Oceans Changing Marine
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potential distribution in the German Baltic Sea. Your tasks will include: Compilation of existing monitoring data on seagrass occurrence and coverage, density and composition today and in the past along