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) region, and on synergetic approaches that can extract optimised information from different investigative methodologies. Research will be in liaison with the objectives of the Dust-DN project. Position
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. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model for diagnosis and prognosis of different sarcomas. He/she will develop and train
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be working primarily with scientific machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields
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and development of associated sensing and estimation algorithms Path planning based on medical imaging data (e.g., MRI, CT, angiography) Development of AI-based control methods for continuum robots
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will develop novel and privacy-preserving algorithms that allow distributed devices (smartphones, wearables) to learn from new data streams over time (Continual Learning) while collaborating globally
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formula is true or false (EXPTIME vs NP). Can we develop and implement efficient algorithms for this problem? This problem has been attacked using multiple different methods for the past 40 years, without
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the signal quality of reflective pulse oximeters • You develop electronic hardware with different arrangements of analog front ends, light-emitting diodes, and photodetectors • You record data sets
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About The University Swansea University is a research-led university that has been making a difference since 1920. The University community thrives on exploration and discovery and offers the right
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systems. Responsibilities include: Integration of advanced sensing technologies with continuum robotic systems and development of associated sensing and estimation algorithms Path planning based on medical
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to facilitate perceptual learning of different stimulation patterns; and (iii) the development of advanced AI algorithms capable of converting camera input into real-time electrical stimulation parameters. In