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interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life-science
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of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD project falls under the collaboration between
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. The objective is to develop models and algorithms that capture spatial variability, uncertainty, and communication constraints, and to understand how these factors influence perception, adaptation, and
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, computer science, and statistics The objective of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD
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in the inner ear and signal treatment algorithms assist in preparation and testing of the microelectrode arrays at the partner institution collaborate with an interdisciplinary research team in a
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Department of Electronic
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Assistance in Complex Acoustic Environments within the general study programme Electrical and Electronic Engineering. The PhD Stipends are open from August 1, 2026, and the integrated PhD stipends are open for
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Job Description Join a young research group dedicated to transforming materials discovery from empirical exploration to predictive design. Our research program builds on a synergy of high-throughput
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interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life
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. The candidate will design models and algorithms for learning and decision-making under uncertainty, optimized for real-time operation on heterogeneous physical devices. Finally, the position will address how