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to leverage high-throughput phenotyping to create knowledge about plant function at the physiological level and use forward genetics approaches to unravel the genetic architecture of root traits. Our most
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. This research direction requires advancements in modern probabilistic tools, including spatial random graphs, random walks, and Markov chains. The position is hosted in the Leibniz Junior Research Group
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With its work, the Leibniz Institute of Vegetable and Ornamental Crops (IGZ) contributes to a better understanding of plant systems and thus to the development of sustainable and resilient
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hold a MSc in plant science, crop science, biology, or related field. You have experience growing, managing, and phenotyping plants in the field and greenhouse. You have experience using modern
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, and other scientific events Your qualifications and skills: You hold a MSc in plant science, crop science, biology, or related field. You have experience growing, managing, and phenotyping plants in
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At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13 TV-L, part
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aim to leverage high-throughput phenotyping to create knowledge about plant function at the physiological level and use forward genetics approaches to unravel the genetic architecture of root traits
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screening (Ulrike Haug), prevention and implementation science (Hajo Zeeb, Daniela Fuhr), biostatistics, machine learning, data science and research data management, and causal inference methods (Iris Pigeot
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. The position is part of the research group Quality.2 (Phytonutrient Management) in the programme area ‘Plant Quality and Food Security’ (QUALITY). The aim of the research project ‘GluAmin’ is therefore