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The job information is shown below. Please click on the links to see full details. Applications are invited for the position of Research Fellow in Algorithmic Sensing for Music to create a new
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concepts underlying the GIG into efficient data structures and algorithms. Your work will also involve developing algorithms to manipulate and analyse GIGs, creating efficient methods for translating GIGs
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on the mathematical theory of deep learning as part of the joint NSF-EPSRC project “DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
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advance the fundamental science of artificial intelligence and address some of the field's most important challenges. You will be responsible for researching and developing novel algorithms and techniques
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NSF-EPSRC project “DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks”. The research will involve collaboration with
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fundamental algorithms for producing policies for rich goal structures in MDPs (e.g. risk, temporal logic, or probabilistic objectives), and modelling robot decision problems using MDPs (e.g. human-robot
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conduct cutting-edge research on the interplay of theoretical computer science, mathematics, and quantum mechanics. Particular topics include classical and quantum aspects of: Sublinear algorithms and
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interpretable reduced-order models for fuel cell control using the Sparse Identification of Nonlinear Dynamics (SINDy) algorithm applied to numerical and experimental data. You will work closely with
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demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming
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-world environments. To achieve this, we will integrate multiple radar units into autonomous vehicle platforms and evaluate perception algorithms in diverse scenarios. The successful candidate will work