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-on experience with experimental gas neutralization setups. Proficiency in mineral characterization tools (XRD, XRF, TGA, SEM). Proficiency in laboratory analysis techniques (pH, ion chromatography, titration, ICP
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surfaces using surface chemistry and interfacial analysis techniques. Contribute to the optimization of flotation process parameters based on experimental results. Work closely with a multidisciplinary team
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processes, or energy management. Preferred Skills: Experience with time-series analysis, predictive modeling, and anomaly detection. Familiarity with real-time applications of AI/ML in embedded or IoT devices
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. Additional Skills (Preferred): Experience with environmental data analysis (R, multivariate statistics). Experience in GIS. Strong scientific writing skills and command of scientific English. Initiative
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person Tentative Schedule: Year 1 1 Collection of flux data B isotopic analysis, macro- and micronutrient analysis Monitoring and analysis of flux data 2 Collection of flux data B isotopic analysis, macro
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for the design, analysis, and optimization of energy networks in urban environments. We are seeking a dynamic and motivated specialist to join our research team on urban energy networks management. The selected
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bioengineering. Performing microbiological analyses to assess soil health and carbon sequestration (microbial biomass analysis, soil enzyme activity assays, microbial community profiling,quantification of soil
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efficient and scalable algorithms that can handle large-scale datasets. Tensor Analysis: Analyze the structure and properties of multidimensional networks represented as tensors. Investigate different
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or membranes. Proficiency in advanced characterization techniques, such as BET, FTIR, XRD, SEM, TEM, TGA, ICP, and gas sorption analysis. Good understanding of process design for adsorption or membrane-based
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of Computational Biology, or related fields Strong publication record in leading international journals Excellent background in molecular biology Excellent programming skills Experience in computational analysis