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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high
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relationships between them. Possible directions for the project include (the final scope will be developed together with the candidate, and it is not necessary to cover all topics): Group fairness: developing and
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 2 months ago
control applications. 2. Control Design nonlinear optimal control algorithms. Investigate advanced control strategies for compliant robotic manipulation. 3. Experimental Validation Validate the developed
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systems, or continuous-time and discrete-time LTI systems theory is a plus. Experience with mathematical modeling, optimization, numerical computation, algorithm development, or machine learning. Prior
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on this project, you will: develop mathematical theory for non-linear inverse problems governed by wave equations; design and analyse numerical algorithms for inverse problems, uncertainty
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conditions as well as in relevant real-world environments, Design and conduct listening tests to investigate the subjective preferences of users under various conditions, Develop DSP algorithms to be
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level, from the quantum processor to the quantum-classical interface all the way to quantum algorithms and applications. The vision of the programme is to enable the development of fault-tolerant quantum
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Uppsala University, Department of Information Technology Are you interested in probability theory, statistics, and mathematical modelling? Would you like to develop new methods for uncertainty
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algorithms on a four qubit quantum processor, realized baseband control of single spins, and demonstrated entanglement between remote spin qubit registers using spin shuttling. As a PhD researcher, you will
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to accurate sample reconstructions using advanced signal processing and tomographic reconstruction algorithms. With the inclusion of noise the object estimation accuracy will be based on statistical concepts