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Are you interested in the future of Plant Breeding and exploring the genetic potential of plants to develop resilient crops for a sustainable agriculture? Then this vacancy may be of interest to you
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, you will design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale
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Postdoc Position in AI Foundation Models for Crop Microbiomes Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application
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crop monitoring and decision-support systems for Controlled Environment Agriculture (CEA). This project focuses on the development, validation, and integration of non-destructive plant sensing
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crop monitoring and decision-support systems for Controlled Environment Agriculture (CEA). This project focuses on the development, validation, and integration of non-destructive plant sensing
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Join the M-WAVE team to develop a forward operator for land data assimilation. Job description Challenge: Understanding the climatic drivers of crop failure, monitoring crop growth and implementing
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approaches in plant breeding, offers new opportunities to address this. One such challenge is to improve complex traits such as crop tolerance to dynamic environmental conditions in the current era of global
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microbiomes to adapt to environmental change. Ancient environmental DNA (eDNA) provides a unique record of past ecosystems, preserving genetic traces of microorganisms and plants that interacted with crops and
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such challenge is to improve complex traits such as crop tolerance to dynamic environmental conditions in the current era of global climate change and how to best incorporate this in plant breeding strategies
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Take the next step in your research career and contribute to pioneering discoveries at the forefront of plant immunity, effector biology, and sustainable crop improvement. The molecular interaction