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collaboration funded by the French National Research Agency (ANR) and the Swiss National Science Foundation (SNSF). The project brings together expertise in multifractal analysis, urban and energy planning
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field (e.g., Environmental or Soil Sciences, AI, Data Science, Geosciences). Basic knowledge of soil science and strong interest in AI and soil health. Experience with data analysis/modelling and
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have the opportunity to exploit some of the cutting-edge experimental and computational methods, comprising constraint-based and kinetic modeling, statistical analysis of large datasets, high-throughput
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Programming skills (commonly C++, Python, or similar languages used in HEP frameworks), Monte Carlo simulation methods and data analysis techniques Interest in connecting ideas and people across disciplines
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related field Strong Python programming skills and experience with PyTorch or TensorFlow Interest in multimodal data, time-series analysis, or NLP Excellent English; German or French is an asset
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biochemical models, data assimilation, spatial analysis and GIS approaches. • Programing skills (e.g. R or Python) for data manipulation and visualisation, and to perform statistical analysis (e.g. mixed models
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and quantity bioaerosols To employ data analysis and bioinformatics to extract bioaerosol characteristics To apply source tracking tools to identify the sources and quantify the contributions To employ
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. Empa is a research institution of the ETH Domain. To strengthen our team and enhance our knowledge and understanding in pyrolysis processes we are looking for a PhD student for scientific analysis
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talented candidate with a Master’s degree in civil engineering, mechanical engineering, or a related discipline Solid background in mechanics of materials and finite element analysis Sound knowledge
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laboratory analysis, including generating isotopic or trace element data You have strong quantitative skills and comfort with coding, and good analytical thinking You are committed to working in