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sensor data, public databases, and GIS. Predictive Modeling:Design predictive models to evaluate the impact of urban and environmental policies on public health. Interdisciplinary Collaboration:Collaborate
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calculations to model and optimize heterogeneous catalysts. Conduct simulations to evaluate catalytic performance and reaction mechanisms. Analyze and interpret computational data to understand the interactions
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, synthesize, and characterize advanced materials for biomass conversion. Conduct experiments to evaluate the performance of these materials in various conversion processes. Investigate the mechanisms of biomass
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skills are expected: PhD in Chemical Engineering, Materials Science, Chemistry, or a related field. Expertise in adsorption or membrane-based separation technologies (e.g., gas separation, water treatment
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: The successful postdoctoral applicant will manage an exciting project on hybrid FO-RO desalination system and small-scale testing for seawater desalination applications. The candidate should have a PhD in
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talented Postdoctoral researchers in the area Blockchain and IoT. The successful candidates will primarily be working on the following topics (but not limited to): Quantum Cryptography IoT Security
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foundation in catalysis/ separation and chemical/process engineering. The successful candidate will significantly contribute to the conception, synthesis, and evaluation of separation/catalytic systems aimed
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component. The battery management system (BMS) unit is not just a component, but a crucial element tasked with monitoring each cell of the battery and running algorithms to calculate state of charge (SoC
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: PhD degree in Materials Science, Chemical Processes or another suitable engineering discipline. Sound background in Catalysis Experience in process engineering including one of these areas: urea
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challenging task. In most cases, only a sample of a network is observed. Therefore, network completion needs to be addressed. Matrix completion methods have proved to be efficient when reconstructing a non