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with colleagues at DTU and IIT Bombay, as well as with academic and industrial partners globally. The main purpose of this PhD position is to develop, implement and assess machine learning models
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optimization. We are looking for a candidate who is motivated by both technical curiosity and making a real-world impact. Ideally, you: Have experience with AI models (e.g., graph neural networks, supervised
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products under different operating conditions. Testing new bioreactor configuration for carbon dioxide biological conversion. Modelling carbon dioxide fermentation to acetic acid. Contribute as teaching
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(ORR), oxygen evolution reaction (OER), and carbon dioxide (CO₂) reduction. Collaborating with theoretical research groups to guide the design of active site structures through computational modelling
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restraint conditions. A key goal is to develop both a sensor system and a prediction model for the short- and long-term deformation behaviour of concrete. These tools will be applied to full-scale structural
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intelligence. This PhD project will leverage the power of field-programmable gate arrays (FPGA) to deploy machine learning models on the edge with low latency and high energy efficiency. This added intelligence
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background in Computer Science, Informatics Engineering, Mathematical Modeling, Computational Urban Science, Transport Modeling or equivalent, or a similar degree with an academic level equivalent to a two
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scientists covering a broad range of expertise in photonics and electronics. The Project in Short The project focuses on developing numerical modeling and optimization tools to explore the information
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to be cost competitive with other technologies, long lifetime of >5 years operation under high current density is desired. Operation conditions such as temperature, gas composition, current density and
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bottlenecks in data and system management, especially around data quality, metadata governance, and the integration of machine data for long-term monitoring. Through a hybrid approach combining physical models