10261 - Research Associate
| Posting date: | 16 April 2024 |
|---|---|
| Salary: | £39,347 to £46,974 per year |
| Hours: | Full time |
| Closing date: | 14 May 2024 |
| Location: | Edinburgh, Scotland |
| Remote working: | On-site only |
| Company: | University of Edinburgh |
| Job type: | Temporary |
| Job reference: | 10261 |
Summary
The School of Informatics, University of Edinburgh invites applications for a postdoc to undertake novel research at the intersection of computer vision and machine learning. The candidate will be based in Visual Computing Group (https://groups.inf.ed.ac.uk/vico/) and will be supervised by Dr. Hakan Bilen. There will be many collaborative opportunities both within the school as well as with the University of Oxford and Bristol.
The Opportunity:
The goal of this project is to develop novel techniques for training deep neural networks efficiently. This will involve generating data for training, sampling informative samples and designing data-efficient architectures for various vision models, and also vision-language models.
To apply please include:
a brief statement of research interests (describing how past experience and future plans fit with the advertised position)
complete CV, including list of publications
the names and email addresses of two references.
This post is full-time (35 hours per week), with a fixed term end date of November 2025 with the possibility of extension. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working.
Your skills and attributes for success:
PhD degree (or nearing completion)
A strong background in machine learning and/or computer vision
Publications at top venues in CV or/and ML (e.g., CVPR, ECCV, ICCV, NeurIPS, ICLR, ICML)
Excellent programming skills in Python, PyTorch, Tensorflow
Ability to work independently and manage own academic research and associated activities.
Excellence in written and oral communication, analytical, and time management skills.
The Opportunity:
The goal of this project is to develop novel techniques for training deep neural networks efficiently. This will involve generating data for training, sampling informative samples and designing data-efficient architectures for various vision models, and also vision-language models.
To apply please include:
a brief statement of research interests (describing how past experience and future plans fit with the advertised position)
complete CV, including list of publications
the names and email addresses of two references.
This post is full-time (35 hours per week), with a fixed term end date of November 2025 with the possibility of extension. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working.
Your skills and attributes for success:
PhD degree (or nearing completion)
A strong background in machine learning and/or computer vision
Publications at top venues in CV or/and ML (e.g., CVPR, ECCV, ICCV, NeurIPS, ICLR, ICML)
Excellent programming skills in Python, PyTorch, Tensorflow
Ability to work independently and manage own academic research and associated activities.
Excellence in written and oral communication, analytical, and time management skills.