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Field
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enables the Faculty to assess performance against the highest international standards. It also creates an exciting environment of continuous improvement. FEB's programmes, academic staff and research do
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of robotics, electromobility and autonomous driving. We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and
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processing, signal processing, network resource management to improve the performance of the future wireless communication systems. Finally, due to the large-scale nature, complexity, and heterogeneity of 6G
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an ARC Discovery Project in conjunction with support from Curtin University. The purpose of the scholarship is to support a PhD student to carry out research in quantum collision theory. Currently
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nanotubes. The most efficient catalysts will be characterized ex situ by electron microscopy and x-ray photoelectron spectroscopy, and under operating conditions by X-ray absorption spectroscopy (XANES and
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affect surface outcomes, benchmark against conventional techniques, and evaluate performance of the finished components. You’ll also delve into intelligent automation and machine learning to optimise
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Job Description Are you driven by the idea of creating a more sustainable future through groundbreaking research? Do you want to work in a collaborative environment where your contributions can
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PhD Position: Activating Heritage as a Mediator for Dialogue and Belonging in an Era of Polarization
relevance. This PhD project combines locally grounded research in the Frisian context with strong international academic exchange. It offers the opportunity to work closely with regional stakeholders while
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of justice, knowledge and power in agriculture and forestry, natural resource management and development in rural areas. Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en
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. The student will work in a group addressing all these challenges, developing new AI-based methods to improve biological realism in simulations which will lead to more accurately inferred GRNs from real data