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developing new inverse modelling (‘retrieval’) methods to extract 3D information from JWST secondary eclipse observations. The models will be applied to JWST observations of giant transiting exoplanets
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of High throughput Calculations Fluency in relevant models, techniques or methods and ability to contribute to developing new ones High level analytical capability Ability to communicate complex information
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quality modelling approaches to analyse the flow interactions between sewer discharge of surface runoff, as well as the dynamics of pollutants and pathogen propagations associated with water movements. The
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guidance to PhD students where appropriate to the discipline Contribute to developing new models, techniques and methods Undertake management/administration arising from research Contribute to Departmental
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Supervise 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
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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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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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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