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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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set-up, and data collection and analysis. Have the ability to analyse and interpret data using appropriate statistical packages (e.g., conducting linear mixed effects models in R). Have experience
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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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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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the final stages of PhD submission Track record of writing papers as evidenced by publications or submitted manuscripts in referred journals Evidence of data presentation at scientific meetings Excellent
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estimates of disease costs are not well established, with a focus on disease surveillance and control. In the role, you will take responsibility for data analysis and statistical and mathematical modelling
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the Centre for Research Staff Development for more information. About You To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD
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Postdoctoral Research Fellow position is available within the Seed Revolution Lab in the School of Biosciences at the University of Birmingham. The Research Fellow will work as part of the Royal Society-funded
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findings 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