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techniques may be employed to support the modeling of uncertainty, along with the formulation and resolution of planning problems using stochastic optimization methods. Key Responsibilities The selected
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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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) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities: Develop and implement machine learning algorithms for SOC and SOH estimation
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that has been investigated. Fertilization experiments have confirmed that K deficiency limits tree growth and forest productivity and mechanistic models have been developed that confirm the strong response
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alternatives in terms of efficiency, environmental friendliness and sustainability. Job Description CBS is looking for a post-doctoral fellow in process systems engineering, and particularly in modeling
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tools, data science techniques, and spatial analysis to leverage big data from cities and model their evolution. Main Tasks and Responsibilities: Collect, clean, and structure large volumes of urban
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Position Description: We are seeking a postdoctoral researcher specializing in urban modeling and cost analysis to develop an innovative model to estimate the direct and indirect costs
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valorization is essential. Required Knowledge: Solid knowledge of acid-base equilibria, and carbonate system modeling. Good understanding of calcium carbonate behavior and dissolution kinetics. Hands
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, comminution modeling, and ore characterization, and will contribute to developing an integrated beneficiation strategy that reduces operational costs, and energy consumption. This research aligns with broader
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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