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Generative models for counterfactual inference in monitoring applications

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

In recent years, we have seen an explosion of machine learning innovations a lot of which have only focused on supervised learning applications with well-defined classification objective. In a lot of these problems we have large amount of stuctured data and we assume that every variation of input that can be observed during the test phase of our system would be observed during the training phase as well. However, this is not a realistic assumption to make in large scale monitoring problems where mistakenly applied black box models can lead to wrong causal estimation, mistaken patient diagnosis, dangerous machine response and misleading inference. To address this issue we will seek to build up on the current understanding of the theoretical and empirical properties of state-of-the-art methods in real time monitoring applications as well as develop novel machine learning tools for addressing different challenges in monitoring applications.

Further information: https://jobs.aston.ac.uk/Vacancy.aspx?ref=R190201

Funding Notes

This studentship provides a maintenance allowance (currently £14,777 per year) and covers tuition fees at the home/EU level. Applicants from outside the EU are welcome but they will need to pay the difference between the home/EU and international fee levels; that difference is currently £12,290/year.

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