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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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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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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
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interest in the human brain. Programming experience (Python, MATLAB) and proficiency in spoken and written English is required. Experience with or an interest in microscopy, quantitative image analysis
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of the selection process. You should also have: Strong analytical skills Strong knowledge in MS Excel and PowerBI or Tableau, as well as in one or more of the following: Python, R, SQL Experience with Machine
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in earth observation data, agriculture and programming languages (e.g. python). Your motivation, overall professional perspective and career goals will also be explored during the later stages
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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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from multiple sources, including earth observation data, IoT-based sensor data, and in situ data Comfortable with programming or scripting in Python or R for data analysis and for bringing your models
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, Computer Science, Data Science, or a related field Experience with machine learning, data analytics, or computer vision techniques Programming experience in Python and familiarity with machine learning frameworks