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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
resistant and susceptible plants. Develop an AI-assisted image-based phenotyping pipeline to automatically quantify aphid performances on the plants. This software will automatically count for aphids and
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resistant and susceptible plants. Develop an AI-assisted image-based phenotyping pipeline to automatically quantify aphid performances on the plants. This software will automatically count for aphids and
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Applications are invited for a postdoctoral position in the group of Dr Aleksandr Gavrin ( https://mbg.au.dk/a-gavrin/ ) at the Department of Molecular Biology and Genetics, Aarhus University
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Systems: https://www.cs.aau.dk/research/distributed-embedded-intelligent-systems/ The Department of Computer Science features a broad range of synergistic activities within research and education in
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quantitative genetics or animal breeding Has published high-quality research in peer-reviewed journals Experience with scripting languages (e.g., R, Python, SAS) and/or genetic software (e.g., DMU, ASReml) Can
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and Distributed Systems: https://www.cs.aau.dk/research/distributed-embedded-intelligent-systems/ The Department of Computer Science features a broad range of synergistic activities within research and
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an LLM-assisted software framework for first-principles simulations, thereby gaining extensive experience within scientific software development and AI-driven workflow automation. The work will initially
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QGG Aarhus University seeks two Postdoctoral researchers in Quantitative Genetics of sustainable ...
quantitative genetics or animal breeding Has published high-quality research in peer-reviewed journals Experience with scripting languages (e.g., R, Python, SAS) and/or genetic software (e.g., DMU, ASReml) Can
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employment is 2 years. You can read more about career paths at DTU here . Further information Further information may be obtained from Andrey Rivkin, DTU Compute, https://orbit.dtu.dk/en/persons/andrey-rivkin
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collaboration with local water utilities and software developers Integrate digital urban water twins with data, applying methodologies for data assimilation, parameter estimation, and quantification of model