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Field
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consisting of PAT and mechanistic / data driven modelling allowing process control. Steps to be taken will be: Developing a process applicable PAT method (single / multisensoric) for AAV / LNP / VLP detection
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renewable energy, AI-driven engineering, and industrial research. Cranfield’s expertise in wind energy systems, predictive maintenance, and AI applications provides an ideal environment for cutting-edge
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Computational Fluid Dynamics (CFD) and Conjugate Heat Transfer (CHT) modelling, which captures both the fluid & solid domains, as required to develop this understanding for engine-representative geometries and
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project in collaboration with AstraZeneca Chalmers University of Technology, funded through the Wallenberg National Program for Data-Driven Life Science (DDLS). Chalmers University of Technology conducts
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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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., economics, business, technology), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society. For more information, please visit our website: www.uni.lu/snt
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power systems. You will join a large group of postgraduate students in the Faculty of Engineering, working on many aspects of solar energy and zero carbon technologies. The team of potential PhD
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power systems. You will join a large group of postgraduate students in the Faculty of Engineering, working on many aspects of solar energy and zero carbon technologies. The team of potential PhD
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Artificial Intelligence, Stochastic Modeling and Optimization, and Data-driven Decision-making with applications in supply chain and operations management. This position offers an exciting opportunity
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molecular mechanisms that drive its invasive behavior, both general and patient-specific. Using cutting-edge spatial techniques and CRISPR-based methods, we build data-driven models that link gene regulation