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formulation development and product optimization. Ability to design and evaluate the performance of unit operations. Experience in physicochemical characterization techniques (rheology, particle size analysis
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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 estimation of some of the significant water balance components. The candidate is expected to seek an optimal integration between the physical representations of the various processes and the computing power
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, interdisciplinary research team. The position focuses on the development, optimization, and integration of advanced bioprocesses for the bioleaching and biorecovery of rare earth elements (REEs) from secondary
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to microclimatic variations induced by local vegetation. The researcher will contribute to the analysis of vegetation–climate–technology interactions to optimize energy yield in environments subject to climatic
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monitoring and electric vehicle battery tracking. Integrate environmental and energy sensors with real-time data collection and analysis systems. Deploy prototypes in the field and optimize their performance
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advancements and practical implementations optimized for modern HPC systems. The postdoc will primarily contribute to one or more of the following research areas: Development of efficient numerical linear
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experts to integrate LLM-based solutions into predictive maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance schedules. Publish high
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Job Description As part of our laboratory's research initiatives, we are conducting advanced research on the computational modeling and optimization of heterogeneous catalysts for various catalytic
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research team. The successful candidate will work on optimizing methods for nanofibers extraction from various types of biomass, focusing on the development of efficient, sustainable, and scalable processes