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? As a PhD candidate, you will develop an integrated modelling framework to analyze the Water-Energy-Food (WEF) nexus in Controlled Environment Agriculture (CEA), including greenhouse and vertical
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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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Post-harvest pathology Biomarkers, volatiles, and sensors Cold chains and refrigeration technology Data analysis and modelling (R, Python, CFD) Besides that, you have demonstrable experience in project
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Job description Recent trends in Controlled Environment Agriculture (CEA) development, design, and operations related to energy saving and greenhouse gas emission reduction, are mainly focused
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sources or related laboratory hardware. You are interested in instrument automation and quantitative data analysis. Experience with Python, LabVIEW, or Matlab for instrument control/data processing is
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data acquisition or experience in programming and modelling (e.g. Python, MATLAB and LabView) or CAD would be an asset. You should have good interpersonal and communication skills and should be able
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statistical analyses more robust. We are looking for a research assistant to contribute to the development of bamojax(link is external) (Bayesian modelling in JAX), our open-source Python toolbox
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science, spatial analytics, or a related field; experience with diverse spatial analytical methods; strong programming skills (e.g., Python) and version control (e.g., GitHub); experience working with multi
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steps. You have experience with R or Python and feel comfortable working with large language models or you would like to develop your skills further in these areas. You ask critical questions about AI