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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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, or biophysics. Experience with experimental organic chemistry, NMR, kinetic modelling and/or cheminformatics are advantages. The candidate must be able to work independently, but also participate in
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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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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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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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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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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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properties of skeletal muscle during static and dynamic contractions. The student will also participate in early-stage algorithmic work to model muscle architecture and behavior across contraction types. In
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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