Research Fellow

Contract Type: Fixed Term contract up to August 2025

Closes: 14^th April 2024

Travel and International travel may be required for this role.

The University of Birmingham is looking to recruit a Research Fellow based at the School of Computer Science. The successful applicant will work on an EPSRC funded project, which aims to develop advanced machine learning algorithms to understand how the Earth’s climate and ecosystem have been changing and how they are impacted by human behaviour. The applicant will focus on developing transfer learning approaches to train and evaluate models with environmental data from multiple sources, through close collaboration with McMaster University, Canada.

The Research Fellow will be responsible for: undertaking day-to-day responsibility for developing and evaluating machine learning models; providing regular analysis and updates for the principal investigator and the project partner; participating in project team meetings; disseminating research findings through publication, posters, research seminars etc. The Research Fellow will benefit from a range of training and supervision opportunities (e.g., Artificial Intelligence seminar series and potential PhD supervision) while in post and will work as part of an interdisciplinary team made up of computer scientists and civil engineers. In your application please include a cover letter stating how you match the person specification.

Person spec

• First degree in area of Computer Science or related discipline and normally, a higher degree relevant to Machine Learning and Artificial Intelligence or equivalent qualifications
• Demonstrable knowledge of machine learning methods (ideally transfer learning) for classification or regression problems.
• Strong programming ability in Python and practical knowledge of current machine learning or deep learning libraries and frameworks.
• Ability to disseminate research findings through publication and/or oral presentations.
• Ability to communicate effectively with colleagues from different academic disciplines and deliver information clearly.
• Self-directed, flexible approach to work.
• Co-ordinate own work with others to avoid conflict or duplication of effort.

Informal enquiries to Dr. Wang: s.wang.2@bham.ac.uk.

To download the full job description and details of this position and submit an electronic application online please click on the 'Apply' button.

Valuing excellence, sustaining investment

We value diversity and inclusion at the University of Birmingham and welcome applications from all sections of the community and are open to discussions around all forms of flexible working

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