Research Associate/Senior Research Associate in Machine Learning and Artificial Intelligence (multiple positions)

Updated: about 2 months ago
Location: Bristol, ENGLAND
Job Type: FullTime
Deadline: 16 Sep 2021

The role

The UKRI Turing AI Fellowship Interactive Annotations in AI ( ) focuses on developing novel approaches to human-centric machine learning. The team studies complex forms of interaction between AI systems and humans to build trust and accountability. In particular, we develop methods for humans to provide informative and actionable feedback in order to shape the behaviour of AI systems, allowing humans in return to fully understand and measure the effect of their contribution. The project works with industrial partners and academic collaborators across multiple fields, including healthcare, IT, engineering and social media.

Within this exciting interdisciplinary project, we are looking for exceptional candidates to strengthen our machine learning capability, with interests that spread through one or more of the following areas:

  • Human-centric machine learning, including interpretability and explainability / accountability and transparency.
  • Foundations of statistical learning theory, optimisation and game theory in AI.
  • Applied machine learning, particularly in (but not limited to) the healthcare domain.
  • Human computer interaction and experimental psychology in the context of machine learning.

The post-holders will join a multidisciplinary team, working with machine learners, data scientists, software engineers, clinical and industrial partners. We support and encourage diverse applicants and career paths and provide an inclusive research environment within the Intelligent Systems Laboratory. We are also happy to consider flexible working or part time arrangements. 

What will you be doing?

Your main responsibilities will be as follows:

  • To perform theoretical or applied research in key areas of the human-centric machine learning (explainability, interpretability, accountability and transparency), machine learning evaluation and game theoretical AI.
  • To implement these procedures and techniques in state-of-the art machine learning toolboxes.
  • To publish the work in top journals and international conferences, and present in seminars and workshops.
  • To participate in regular workshops, project meetings, and contribute to the day-to-day activities of the team.

You should apply if

  • You have a strong research track record in machine learning and AI or related areas, with an excellent and broad conceptual and practical knowledge of the state of the art, and a desire to push the boundaries of research.
  • You combine fundamental research skills and knowledge with experience in machine learning software development and deployment in practice. Industry experience or expertise in the healthcare domain are particularly relevant.
  • You have published in relevant top conferences such as ICML, ECML-PKDD, Neurips, ICLR, UAI, KDD, COLT, IJCAI, ECAI, AAAI, FAccT, AIES; and/or relevant top journals.
  • You are self-motivated and independent but also able to work as part of a team.

Additional information

For informal queries, Dr Raul Santos-Rodriguez,

To find out more about what it's like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog:

We welcome applications from all members of our community and are particularly encouraging those from diverse groups, such as members of the LGBT+ and BAME communities, to join us.

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