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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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machine learning methods to improve the understanding, treatment and prevention of human disease. The successful candidate will develop novel statistical and machine learning algorithms to address key
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type (iv) work with the computational biology team to transfer this information into a AI algorithm that can distinguish neurodegenerative and neuroprotective phenotypes (v) work with colleagues in
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developing data analysis approaches and contribute to the overall study design and implementation. In particular, this will involve applying existing or even developing new algorithmic approaches for TAPS data
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developed goal-sequence generalization task. The project will integrate high-density silicon probe recordings, optogenetics, pharmacology and advanced computational tools to analyse neural algorithms
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Trust and is fixed-term for three years. This research position aims to develop machine learning algorithms to enable learning human ethical values from survey data. The postdoctoral researcher will
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endoscopists through a quantitative and qualitative assessment of the mucosal microstructure. You will be responsible for the algorithm development and implementation of the overall system. It is expected
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for coordinating grid-edge flexibility, and contribute to the development of a software platform for algorithm design, training and benchmarking. You should possess the following skills and experience
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methodologies, algorithms and tools for data analysis and dissemination. As part of PROTECT you will interact with various scientist to transfer protocols, help develop research questions, to present results and
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thermal load in superconducting quantum circuits. The successful candidate will develop new characterization and benchmarking techniques for quantum algorithms on devices at or beyond the 16-transmon scale