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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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scientists on, e.g.: Developing self-supervised learning frameworks to extract features from unlabeled high-resolution microscopy data Training and evaluating segmentation models for detecting and
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research together with cutting-edge materials science and physics. Depending on your background you will work collaboratively on the following tasks with either with a stronger model-development or
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plant genetic mechanisms that coordinate mycorrhizal interactions with plant P and water status, root system development, and soil microbial communities. Using maize and rice as models, we will: 1
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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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Description 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
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plant genetic mechanisms that coordinate mycorrhizal interactions with plant P and water status, root system development, and soil microbial communities. Using maize and rice as models, we will: Determine
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, crystallization, or molecular aggregation/switching. The BEAM projects cover a wide spread of topics, including theoretical physics and chemistry work. For example, our targeted syntheses are supported by models
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the training of state-space models Collaborate closely with our internal partners at PGI-14 (Neuromorphic Hardware Nodes) and international academic and industry partners Publish research articles and regular
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resource-efficiency requirements. This collaborative doctoral project brings together the Institute of Advanced Simulation – Materials Data Science and Informatics (IAS-9) and the Institute of Energy