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mark on the national, continental, and global stages. Job Description: We are seeking a postdoctoral researcher specialized in the modeling and optimization of waste management systems. The successful
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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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multiplex and multilayer networks alongside with the observed links in order to predict or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor
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associations, and the surface properties of the minerals. In general, a mineral cannot be floated even if the processing conditions are optimized if it is locked (encapsulated). To improve flotation recovery
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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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, simulation and optimization of the phosphate value chain processes. In terms of research, the candidate will reinforce the team of the CBS department. His/her experience and expertise should enable him/her
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optimizing treatment processes that use calcium carbonate-rich materials extracted from phosphate mine waste. These materials will be assessed for their capacity to neutralize acid gases (SOx, HF) emitted from
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industrial processes. Optimization of Industrial Processes: Utilize nuclear techniques to enhance the efficiency and sustainability of industrial processes. Collaborate with production teams to integrate
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algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be on creating and optimizing state-of-charge (SOC) and state-of-health (SOH
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Postdoctoral Researcher positions to support its growing research portfolio in renewable energy-driven water production and condensation-based system optimization. The positions are designed for early-career