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recording. Actively engaging and working closely with our multidisciplinary team of PhD students and postdocs to support them with their own analyses and perform analyses for their projects. Performing
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per week) Participate in academic self-governance Completed relevant university degree (Master's or equivalent) and a completed PhD in sport science, psychology, or a related field Experience in data
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Mentoring and advising PhD students and postdoctoral researchers Publishing first-author manuscripts and presenting work at international conferences PhD in Computational Biology, Bioinformatics
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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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of the research initiative. In addition, you will have opportunities to develop e large collaborative projects with forest network partners, including members of the ForestPlots network. You hold a PhD in forest
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. Authoring and co‑authoring peer‑reviewed scientific publications and presenting results at international conferences. Profile PhD in Environmental Science, Environmental Engineering, Ecology, Ecohydraulics
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their PhD by the start date. Relevant fields include behavioral marketing, psychology, experimental economics, quantitative marketing, or computer science. For Project A, experience with natural
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profile We welcome applications from candidates who will have completed their PhD by the start date. Relevant fields include behavioral marketing, psychology, experimental economics, quantitative marketing
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 2 months ago
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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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