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“learning from nature” approach to explore how novel protein crops and their close relatives interact with neighbouring plants and the wider ecosystem, translating these insights into biodiversity-positive
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PhD Candidate on The Future of Mixed Methods Research /Junior Lecturer in Methodology and Statistics
support senior teachers and offer guidance. You teach qualitative research methods and general courses in research methods in the programs in which the Methodology and Statistics department is involved
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University & Research (WUR). The Laboratory of Biophysics focuses on studying and developing an understanding of the physical aspects of life processes and to teach the fundamentals of physics and biophysics
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to acquire and develop reflexive, participatory and transdisciplinary research skills. You will be part of a vibrant and supportive interdisciplinary, international community at the Copernicus Institute
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opportunities for co-developing multispecies governance approaches with representatives of governance bodies and identifying ways to transform towards them. Finally, we will synthesize our learning across cases
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on the latter; identification and characterization of the products you obtained using a multitude of analytical tools, for which we are expertly equipped; setting up, executing and interpreting experiments with a
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, sociology, health psychology) who demonstrates a large set of the following qualities: Strong quantitative skills with enthusiasm for real-world data and modern analytic methods; proficient in R. Meticulous
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, bioinformatics, and food-quality research. You have strong analytical skills, good communication abilities, and you are comfortable collaborating across research groups and research environments (lab, greenhouse
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perspective. The second PhD position within this work package will focus on ‘learning from nature’. Together, these complementary perspectives will contribute to an integrated, system-level approach
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layers across heterogeneous platforms. Ideally you would have familiarity with deploying or supporting AI and machine-learning workflows, including large models, large network analytics, or multimodal data