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Postdoctoral Research Associate

University of Exeter – Faculty of Environment, Science and Economy

Faculty of Environment, Science and Economy

The above full-time post is available immediately, on a fixed term basis until 31/07/2025, with a possible extension depending on funding.

The post

The Faculty wishes to recruit a Postdoctoral Research Associate to support the work of Dr Zeyu Fu. The researchers will be based at the Department of Computer Science, part of the Faculty of Environment, Science and Economy, and will be associated to the Institute of Data Science and Artificial Intelligence at the University of Exeter.

We are seeking a highly motivated and skilled postdoctoral researcher to join our team to work on multimodal AI for video understanding. The successful candidate will be responsible for conducting cutting-edge research in machine learning, multimodal data analysis, and video understanding applied to social media data.

Responsibilities:

  • Conducting research on the development and application of machine learning algorithms and computer vision techniques to large-scale multimodal datasets from social media platforms.
  • Collaborate with research team members to design and implement data-driven studies to analyse data on social media platforms such as Tiktok.
  • Collect and analyse large datasets using statistical and computational techniques, and communicate findings effectively to both technical and non-technical audiences.
  • Publishing high-quality research articles in top-tier journals and conferences, and presenting research findings at national and international conferences.

The successful candidats will have access to state-of-the-art computing resources, a supportive and inclusive research environment, and opportunities for professional development and advancement.

If you are passionate about multi-modal data analysis, machine learning, and video understanding, and are interested in working on cutting-edge research projects, we encourage you to apply.

About you

The successful applicant will be able to present information on research progress and outcomes, communicate complex information, orally, in writing and electronically and prepare proposals and applications to external bodies.

Applicants will possess a relevant PhD (or nearing completion) or possess an equivalent qualification/experience in a related field of study and be able to demonstrate sufficient knowledge in the discipline and of research methods and techniques to work within established research programmes.

Essential requirements:

  • An excellent track record of publishing/presenting papers in top-tier conferences or journals in the related areas (e.g., computer vision, machine learning, natural language processing or speech analysis).
  • Excellent mathematical and programming skills Python, C, Matlab, or other relevant programming languages with experience deep learning frameworks (e.g. PyTorch and TensorFlow)
  • Excellent written, verbal communication and collaboration skills, with a proven ability to work effectively as a team player. 

Please ensure you read the Job Description and Person Specification for full details of this role.

To find out more about what we offer our staff, please visit: Benefits | Prospective Staff | University of Exeter

The University of Exeter

We are a member of the prestigious Russell Group of research-intensive universities and in the top 200 universities in the world (Times Higher Education World University Rankings 2024 and QS World University Ranking 2024). 

Our Equality, Diversity and Inclusion Commitment

We are committed to ensuring reasonable adjustments are available for interviews and workplaces.

Whilst all applicants will be judged on merit alone, we particularly welcome applications from groups currently underrepresented within our working community. 

Further information

For further information please contact Dr Zeyu Fu, e-mail: z.fu@exeter.ac.uk

Location: Devon, Exeter, Hybrid
Salary: The starting salary will be from £32,982 on Grade (E), depending on qualifications and experience.
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 8th August 2024
Closes: 28th August 2024
Job Ref: R92481
   
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