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nanoparticles and reactions at the atomic-level by combining path-breaking advances in electron microscopy, microfabricated nanoreactors, nanoparticle synthesis and computational modelling. The radical new
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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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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 and machine
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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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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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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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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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computational tool in the near term. The project will focus on Gaussian Boson Sampling (GBS), which is a specialized photonic quantum computing model with demonstrated experimental realizations and proven
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an efficient AI foundational exploration of the molecular space. How can we bias the generative models towards desirable molecular properties How can we integrate generative AI models and different molecular
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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