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foundation in at least one of the following areas: computer vision, computational imaging, computational biomechanics, applied mathematics and statistical modelling, focusing on algorithm design and clinical
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. The BASP laboratory is developing cutting-edge research on all aspects of computational imaging, from theory and algorithms, to applications in astronomy and medicine. Dr Wiaux is a Professor in the School
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on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems tailored to dynamic, human-centered environments. They may also work with diverse signal modalities, including vision
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applications for a Postdoctoral Researcher position. The selected candidate will undertake both collaborative and self-directed research on mathematical modeling, optimization and simulation models/algorithms
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advantages. We will provide the necessary hardware and software for the real-time control of the machine, but the candidate will be responsible for developing and implementing the control algorithms. A working
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, and data analysis for human subjects research. · Develop and apply computational models and algorithms to support robotic augmentation studies. · Contribute to manuscript preparation and dissemination
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or equivalent Skills/Qualifications The post-doc is expected to independently design, plan and conduct experiments. In addition, will oversee the work of the PhD student. Responsibilities: -To develop algorithms
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obtainable using the Oxford Nanopore sequencing platform and improve genome recovery from metagenomes by developing new binning algorithms based on machine learning. Furthermore, the postdoc will aid in
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) determine, using sensitivity analysis, impact of the individual process parameters on the target properties and develop predictive machine learning model; iii) based on the machine learning algorithms
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through advances in statistical and mathematical AI and ML theory and algorithms. Examples of topics of interest include: statistically-principled methods for uncertainty quantification; operator learning