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of field campaigns, data collection and lab work, Spectral data analysis, data processing, and model development, ‘R’, Python programming / package development, Co-supervise PhD and undergraduate students
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Expected Start Date: October 2025 Job Description We are seeking a highly motivated postdoctoral researcher with expertise in vanadium and rare-earth element (REE) recovery, thermodynamic modeling
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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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crop nutrient management assessments. Contribute to the development of spectral libraries and hyperspectral imagery for soil fertility mapping and crop monitoring. Disseminate research findings through
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emissions modeling. Simulation & Optimization Framework Build and validate a dynamic simulation model of mine haulage operations. Integrate multi-objective optimization to explore trade-offs across cost
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collection and scenario development. Techno-Economic & Environmental Assessment Model life-cycle costs and greenhouse-gas emissions for IPCC, trolley-assist, battery-electric trucks, etc. Perform sensitivity
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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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of process modeling software (e.g., Aspen Plus, COMSOL, or equivalent) is a plus. Excellent written and oral communication skills in English. Ability to work independently and as part of a multidisciplinary