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material intralogistics handling alternatives such as trolley-assist systems, battery-electric trucks, and in-pit crushing & conveying (IPCC), combining life-cycle analysis, and dynamic simulation
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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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and compare material intralogistics handling alternatives—such as in-pit crushing & conveying, trolley-assist systems, and battery-electric trucks—in strip mining operations. This research is part of
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: PhD in solar energy, electrical engineering, or environmental sciences. Proficiency in PV systems, instrumentation, and performance measurement. Experience in processing environmental data (Python, R
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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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such as air quality monitoring, water leak detection and energy monitoring of electric vehicle batteries. The candidate will need to master sensor technologies, embedded systems, and communication protocols
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operate lab-scale BMED setups, including multi-compartment electrochemical cells. Test and characterize membranes: transport properties and selectivity. Monitor and analyze system performance: current
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Carry out lab and pilot plant tests to overcome current technical challenges and develop new technologies. Candidate Profile Due to the multidisciplinary character of ACER CoE and IART, the ideal
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submit the following documents: A cover letter detailing your research interests and how they align with the application of LLMs to predictive maintenance. A current CV, including a list of publications
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operate lab-scale BMED setups, including multi-compartment electrochemical cells. Test and characterize membranes: transport properties and selectivity. Monitor and analyze system performance: current