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Field
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-on experience in environmental management. Interdisciplinary training in hydrogeology, contaminant transport modeling, and decision-making. Networking & knowledge exchange with leading academic and industry
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. This project is intended to perform numerical studies and develop a methodology for the numerical analysis aimed at the effective damping of resonance regimes in bladed disks of gas-turbine engines using
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science, data analysis, socio-economically-driven decision-making, and collaborative research, highly sought-after skills. Number Of Awards: One Start Date: Autumn 2025 Award Duration: 4 years Application
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experience with real options analysis, decision making under uncertainty, and/or value chain analysis. Documented experience with the carbon capture and storage sector Recent graduates, or applicants who
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valuable experience in behavioural science, data analysis, socio-economically-driven decision-making, and collaborative research, highly sought-after skills. Number Of Awards One Start Date Autumn 2025 Award
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foundational knowledge in quantitative finance. You will have the opportunity to build alphas on an actual trading strategy. What you can expect Modelling. Apply probability theory, statistical analysis, and
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foundational knowledge in quantitative finance. You will have the opportunity to build alphas on an actual trading strategy. What you can expect Modelling. Apply probability theory, statistical analysis, and
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performance. What you can expect Modelling. Apply probability theory, statistical analysis, and machine learning techniques to analyze and interpret market behavior Alpha Monetization. Blend quantitative
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, optimization techniques, and climate change scenario analysis. The successful candidate will contribute to the development of intelligent models and decision-support tools that enhance the performance
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for carbohydrate characterization, such as Mass Spectrometry (MS) for oligosaccharides and polysaccharides, linkage analysis, substitution patterns, and molecular weight determination, is preferred. Candidates