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’ preferences in terms of ‘productive agriculture’ and ‘healthy biodiversity’ into quantifiable impact indicators; Develop a spatial optimization algorithm that finds land use configurations that optimize
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plants in the automated phenotyping facilities of the Netherlands Plant Eco-phenotyping Centre (NPEC) . Using high-resolution imaging, you will follow plant growth, physiology and disease development after
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development process. Your responsibilities include: Supporting idea development and assessing alignment with national and international funding calls; Identifying suitable funding opportunities and advising
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organic matter degradation processes; Experience or strong interest in synchrotron-based analysis techniques You approach scientific problems with determination and are eager to develop multidisciplinary
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such as publication and patent data, and aims to enrich these with other sources on individual paths and preferences. The PhD candidate will have the opportunity to develop unique datasets and apply
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stakeholders’ preferences in terms of ‘productive agriculture’ and ‘healthy biodiversity’ into quantifiable impact indicators; Develop a spatial optimization algorithm that finds land use configurations
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and disease development after infection with Phytophthora or Ralstonia . You will combine these phenotyping data with bacterial and fungal microbiome profiles to build predictive models of pathogen
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. This is an opportunity to develop substantial experience in qualitative and participatory research while contributing to an emerging research agenda at the intersection of AI, mental health, gender, care
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Are you passionate about developing cutting-edge AI techniques to enhance interaction and communication across multiple modalities, such as text, pictures, audio, and video? Join the large scale
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tests the causal effects of candidate epialleles on gene expression (this PhD project at UU). In this PhD project you will: Develop and use state-of-the-art CRISPR/Cas9-based technologies to target DNA