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-economic metabolism, for example with material flow analysis or life cycle assessment Deep understanding of engineering principles for evaluating novel technologies and provide guidance for their ecological
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the field of environmental politics. Radiocarbon analysis in carbon dioxide (CO2) is the most direct tool to distinguish between renewable sources and fossil fuel combustion, and to support mitigation efforts
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: surface functionalization chemistries, spectrophotometric analysis, analysis of release kinetics and synthesis of hydrogels (nanocomposites). Our offer The work will be carried out at Empa St. Gallen (under
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programming, modelling and data analysis skills in Python and/or R. Experience with the formulation and implementation of mathematical optimization problems can give you a competitive edge. The candidate should
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willingness to learn A solid foundation in experimental research, data analysis, and scientific methods Interest in machine learning and data-driven approaches to materials discovery Strong interest in hands
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Apply machine learning techniques for data analysis and time-series forecasting Collaborate in a multidisciplinary team to accelerate functional thin film development Your work will be part of a larger
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signal processing (GPU based) Proficiency in data analysis using Python, Matlab, or similar Self-motivating, independent-minded scientific researcher, effective collaborator Excellent written and oral