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trolley-assist systems, battery-electric trucks, and in-pit crushing & conveying (IPCC), combining life-cycle analysis, and dynamic simulation. This research is part of OCP’s Strategic Business Unit (SBU
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to join our cutting-edge team, working on the development of advanced AI/ML algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be
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systems, capable of designing and deploying innovative IoT solutions for research projects such as air quality monitoring, water leak detection and energy monitoring of electric vehicle batteries
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. Participation in academic or industrial publications and reports. Profile of the Research Assistant Candidate & Application Materials: Engineering degree or equivalent in Computer Science, Robotics, or Electrical
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documenting experimental research results. Working closely with project partners. Candidate Profile: PhD in solar energy, electrical engineering, or environmental sciences. Proficiency in PV systems
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as well a multidisciplinary scientific profile: PhD degree in Electrical Science, Energy Processes or another suitable engineering discipline. Sound background in Energy systems and Fuel cell hydrogen
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-vis spectroscopy to study their structural, optical, and electronic properties. Fabricate complete perovskite solar cells, followed by detailed electrical performance testing such as current-voltage (J
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alternatives—such as in-pit crushing & conveying, trolley-assist systems, and battery-electric trucks—in strip mining operations. This research is part of OCP’s Strategic Business Unit (SBU) Mining initiative
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and structural analysis using various techniques. Knowledge of advanced structural characterizations (highly valued). Expertise in electrochemistry (including cyclic voltammetry, galvanostatic charge
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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