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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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with deep generative models (VAEs, GANs, diffusion models) or probabilistic modelling is a strong plus. You have good programming skills in Python and experience with a deep learning framework such as
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deep generative models (VAEs, GANs, diffusion models) or probabilistic modelling is a strong plus. You have good programming skills in Python and experience with a deep learning framework such as PyTorch
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skills. experience in data analysis, quantitative modeling and programming (e.g., R, python); knowledge of nutrient and/or agrochemical cycles in agriculture; excellent scientific writing skills in English
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-speaking children and schools and communicating research findings internationally. You have experience with quantitative data analysis, preferably using tools such as R, Python, MATLAB, or similar software
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related discipline; An interest in the impacts of land use; Experience in handling spatial data; Programming experience in Python, and/or R; Proficiency in English; and The ability to work as part of
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; Experience in handling spatial data; Programming experience in Python, and/or R; Proficiency in English; and The ability to work as part of an interdisciplinary research team. The following qualifications
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audiences and collaborate across disciplines; proficiency in spoken and written English. Experience with plant pathogens, microbiome sequencing, image-based phenotyping, R/Python, statistics or machine
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September 2026) in Computer Science, Artificial Intelligence, Applied Mathematics, Hydrology, Civil Engineering, Actuarial Science or a related field; Strong programming skills (Python; familiarity with deep
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background: familiarity with dynamic optimization, cost‑benefit analysis or macroeconomic modelling is an advantage; Experience with programming (Python, R, MATLAB or similar); Ability to collaborate