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to exploit some of the cutting-edge experimental and computational methods, comprising constraint-based and kinetic modeling, statistical analysis of large datasets, high-throughput metabolomics, time-lapse
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Environmental science » Other Mathematics » Statistics Researcher Profile Recognised Researcher (R2) Country Switzerland Application Deadline 9 Mar 2026 - 22:59 (UTC) Type of Contract Permanent Job Status Full
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experiments, experience with online field methods is useful. For both projects, skills in statistical data analyses are important. You enjoy engaging with ideas in depth and are motivated by understanding
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Environmental science » Earth science Environmental science » Other Mathematics » Statistics Researcher Profile Recognised Researcher (R2) Country Switzerland Application Deadline 23 Feb 2026 - 22:59 (UTC) Type
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skills in quantitative data collection, management, and statistical analysis Excellent coding and programming skills (e.g., Python, R, Stata) Strong interest in research in the fields of sustainability
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. For both projects, skills in statistical data analyses are important. You enjoy engaging with ideas in depth and are motivated by understanding concepts rather than simply completing tasks. You are willing
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in planning and conduction of patient-oriented, clinical research projects Very good knowledge of clinical and/or epidemiological study methodology and design Good knowledge in statistical methods and
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independent research interests. Your profile Required: PhD in Marketing/Business/Analytics (or a related field); strong statistical background; proficiency in Python; fluent English. Preferred: experience with
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statistical evaluation Machine learning analyses: implementation of established and new workflows Coordination of activities with Consortium partners, including presentation of results at consortium meetings
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conferences. Enjoy protected research time to pursue independent research interests. Required: PhD in Marketing/Business/Analytics (or a related field); strong statistical background; proficiency in Python