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(Extensive) experience with quantitative methods Experience with or interest in applied scientific research Effective Collaborator: Experience with project-based work, independent planning, prioritising, and
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co-design adapted and new methods to enhance reflection and learning in and adaptive capacity of learning-oriented experiments. The intended start date of your employment is 1 November 2025 and the
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found here . Preferred but not required: Experience with behavioral data analysis, 3D tracking, or video analysis Familiarity with comparative methods, phylogenetic analyses, or statistical modelling
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that field. Your most important activities in this position will be: Developing, improving and harmonising LCA methods, databases and tools to measure environmental impacts in projects in which clients
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interdisciplinary research. In addition, you possess: a completed MSc degree in economics, environmental science, or a related field; a solid foundation in applied quantitative methods (e.g., econometrics, spatial
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optimization models and algorithms to address the above questions. Given the uncertainties involved in food supply chains, we prefer candidates who have a background in (stochastic) optimization methods (e.g
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), sustainable, and climate-adaptive crops. By combining plant biology, simulation modelling, and artificial intelligence we aim to develop smart breeding and cultivation methods. Thus, we try to speed up
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) Proven affinity with the application of statistical methods for data analysis of spatial and temporal datasets in the domain of agronomy, ecology and environmental sciences Proven affinity with modeling
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(LC-MS), you will explore the occurrence, diversity, and transformation of PAs in food matrices. Your research will involve: developing sensitive and selective LC-MS methods using deuterated internal