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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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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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with scientific programming and quantitative data analysis, particularly in Python, is welcomed. Experience with droplet generation, thermal diagnostics, image processing, or automated experimental
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with RTDS/RSCAD, real-time simulation or hardware-in-the-loop set-ups. Software development skills: Python, C, scripting and automation, version control, testing. Expertise in one or more of: converter
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laboratory hardware. You are interested in instrument automation and quantitative data analysis. Experience with Python, LabVIEW, or Matlab for instrument control/data processing is required, but you do not
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comfortable working with optics, fluidics, detectors, light sources or related laboratory hardware. You are interested in instrument automation and quantitative data analysis. Experience with Python, LabVIEW
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related field. You have a strong background in numerical modelling and programming (preferably Python). You will collaborate with colleagues who are AeoLiS and CFD specialists, so affinity with
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requirements and priorities. Strong skills in data analysis, image processing, and programming (e.g., Python/C++). Demonstrated experience in publishing scientific journal papers. Fluent in English (oral and
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mitigation approaches Familiarity with various mitigation regulations and guidelines Familiarity with computational tools such as Python You should also have good interpersonal and communication skills and