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Field
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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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-computer interfaces, cognitive rehabilitation, and neural prosthetics. Your contributions will support the development of a custom CMOS-based SNN processor that can operate in ultra-low-power environments
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for intelligent brain-computer interfaces? We are offering a PhD position in analog/mixed-signal CMOS circuit design for EEG and wearable sensor interfaces, as part of a pioneering project focused on assistive
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a digital format. Computer visions techniques have been recently developed for structural health monitoring of civil structures, including vibration displacement measurements, crack detection and
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Muscle Dynamics: Approximate muscles as “cables” with Hill model dynamics within the SOFA framework. Simulate muscle contraction patterns and their interaction with the larva’s environment, including
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with process safety and security concepts, accident modelling approach, and dynamic Bayesian Networks would be advantageous. Willingness to conduct research in a multi-national project team. Fluent in
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creative – You bring substantial knowledge of statistical (e.g. Bayesian) methods, strong analytical skills, and creativity. Programming skills – You are proficient in Python and/or Matlab. Research
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. You will draw on ideas from Bayesian optimization and Bayesian deep learning, generative modelling, high throughput screening, and combinatorial synthetic chemistry. Responsibilities and qualifications
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, R) Expertise in machine learning, Bayesian statistics is beneficial Capacity for interdisciplinary teamwork and excellent communication skills Ability to communicate in English fluently
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are suitable. The aims of this project are to Review operating characteristics proposed for rare disease trials Develop novel Bayesian operating characteristics for different types of rare disease trials Apply