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Master’s degree in Computer Science, AI, Machine Learning, Mathematics, Electrical Engineering, or a closely related field; or Master’s degree in Medicine (MD) with strong Python skills and some ML
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Required Experience: PhD in Geodesy, Geomatics, Aerospace Engineering, Signal Processing, or a related field Proven experience in GNSS data analysis and processing Very good programming skills (e.g., Python
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agricultural sciences or a related field Several years of research experience in field crop phenotyping Good statistical and programming skills (e.g. in R or Python) Evidence of research excellence through peer
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agricultural, data or engineering sciences, or a closely related field Experience with fieldwork Good statistical skills Programming experience (e.g. in R or Python) Good standard of written and spoken English
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projects initially focused on virus data. This database system is written in TypeScript, React, Kotlin and Python and part of the position is to extend this system. The other part of this position is to
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programming skills in Python Experience with machine learning systems or LLM-based architectures Experience working with complex data systems or developing applied AI prototypes Familiarity with modern AI tools
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software Stata Conducting cluster analysis in Python or R Conducting literature searches and summarising relevant academic research Assisting with the design, implementation, and evaluation of internal
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running data-driven or hybrid hydrological models Strong programming skills (ideally in Python and/or R) Experience in working with large datasets, ideally hydrological, meteorological or climate
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software development of their research. The position focuses on developing Python and C# libraries for research in architecture, civil engineering and extended reality (XR), building on the open-source
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-learning models on distributed systems Strong programming skills in Python and familiarity with a modern ML stack (e.g., PyTorch, hydra, zarr, dask) and best practices MLOps Experience in handling and