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data. Apply knowledge in a way which develops new intellectual understanding. Contribute to developing new models, techniques and methods as required by their research project. Present research outputs
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leveraged to accelerate learning from both classical and quantum data. The project will develop rigorous theoretical frameworks to understand key properties of quantum machine learning models—expressivity
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for publication, research seminars etc Supervise students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and
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Social and Historical Sciences. For more information, please visit http://www.ucl.ac.uk/about UCL Mechanical Engineering has been pioneering the development of engineering education, having taught the core
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statistical models, with the support of project supervisors. Support writing of research outputs for academic and lay audiences, and contribute to the development and running of stakeholder engagement
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Role Description A research position is available to support research to enhance observations of human exposure to air pollution and other pollutants using sensor-based approaches. Air pollution is
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artificial intelligence methodologies. The successful candidate will work at the forefront of computational biology, developing novel approaches for large-scale genomic data analysis and contributing
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of Engineering at the University of Nottingham. The position is part of a larger project in collaboration with the School of Chemistry and you will work in a highly collaborative and interdisciplinary team
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students on research related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration
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life cycle analysis methodologies. Proficiency with modelling and simulation software relevant to TEA and LCA. High analytical ability to analyse and illuminate data, interpret reports, and bring new