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of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict ore quality and optimize operational decisions. 2. Key Responsibilities
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. However, very little work has been performed on system/network optimization while considering the communications requirements jointly with the decision fusion process. This approach will produce novel
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optimization and logistics management. Data analysis and project management skills. Strong understanding of optimization concepts and profitability. In-depth knowledge of environmental sustainability standards
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are seeking a Postdoctoral Researcher specializing in nuclear physics and its applications, with expertise in radiochemistry applied to the phosphate industry. Key Responsibilities Analysis and Monitoring
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, or related fields, demonstrated by publications and/or fieldwork. Experience with qualitative research methods (e.g., ethnography, archival research, spatial analysis). Strong interest in interdisciplinary and
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. The successful candidate will develop advanced machine learning (ML) models to automate and optimize retrosynthetic analysis, facilitating the discovery of efficient and sustainable synthetic routes for complex
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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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their thermophysical properties. Proficiency in computational fluid dynamics (CFD) simulation of thermal energy storage systems, enabling the modeling and analysis of heat transfer, fluid flow, and thermodynamic
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of thermal energy storage systems, enabling the modeling and analysis of heat transfer, fluid flow, and thermodynamic behavior within the storage system to optimize design and performance. Demonstrated
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sampling, analytical methods such as GC-MS, LC-MS, or other relevant instrumentation. Experience in olfactory system research is highly desirable. Background in experimental design, data analysis