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The Network Analysis and Modelling uses machine learning to investigate how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. We are seeking a
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timings) affect the metabolome and proteome of rapeseed seeds. Your findings will serve as molecular fingerprints to support Deep Learning models for hybrid development. Whom we are looking for: An early
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data. You bring first experience with biostatistics methods, e.g. with mixed-models. You are familiar with data analysis using programming languages like R, and/or Python. You have excellent
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microscopy. Root architectural phenotyping. Plant and root physiological measurements to determine the function of root phenotypes. Functional-structural plant modeling to determine the benefit of root