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) to predictive maintenance challenges. Develop and fine-tune LLMs to analyze and interpret unstructured data (e.g., maintenance logs, sensor data, technical reports) for predictive insights Collaborate with domain
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for gas or liquid storage and separation applications. Characterize adsorption and transport properties using advanced analytical techniques. Prepare high-impact research papers for publication in leading
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multisource data (IoT, sensors, satellite images, social media, administrative data). Understanding of urban planning issues (urban forms, basic services, sustainability, resilience). Personal and
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collection and scenario development. Techno-Economic & Environmental Assessment Model life-cycle costs and greenhouse-gas emissions for IPCC, trolley-assist, battery-electric trucks, etc. Perform sensitivity
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infrastructure, mobility, and energy management. Integrate real-time data from sensors and IoT devices to develop dynamic models. Model complex interactions between physical systems (infrastructure) and digital
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set of sensors (LiDAR, RGB, IR, and Spectrometer) that enable advanced plant measurements, that allow us to assess plant’s water budget in response to abiotic stress and nutrients’ application
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of the BMS in lithium-ion batteries, including sensors, actuators, and controllers. In our facility, we are establishing a research unit focused on developing the necessary hardware and software components
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. Additionally, knowledge of gas-phase reaction product analysis using micro-GC and FTIR is essential. A solid understanding of general material synthesis is also mandatory. Candidate Profile: Hold a PhD in
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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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with IoT technologies (smart sensors, connected devices) for real-time monitoring of waste systems. Circular Economy: Familiarity with circular economy principles as applied to waste management