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Research Officer in Machine Learning for COVID-19 detection (0.5 full-time equivalent)
School of Architecture, Technology and Engineering
| Location: |
Brighton - Moulsecoomb |
| Salary: |
£31,406 to £35,326
pro rata
|
| Contract Length: |
2 months |
| Closing Date: |
Thursday 06 January 2022 |
| Interview Date: |
Monday 17 January 2022
|
| Reference: |
TE4033-21-462 |
If you have a once-in-a-lifetime opportunity to make a difference to the lives of many COVID-19 patients, will you rise to the occasion?
In this role, you will be developing novel confidence transfer learning algorithms to convey the 'knowledge' learned from existing well-known respiratory datasets (e.g., asthma, pneumonia, etc.) for cough-based COVID-19 detection (i.e., compensating for the lack of COVID-19 cough samples), while providing a confidence measure for robust and valid predictions. You will also be carrying out research duties (e.g., paper writing, seminar presentations, etc.).
In order to be successful in this post you should have:
- A good (1 or 2:1) bachelor degree in Computer Science or equivalent.
- Sufficient, up to date breadth or depth of specialist knowledge in Machine Learning and interest in COVID-19 detection techniques.
- Competence in Python programming and implementing Machine Learning packages (e.g., Scikit-learn, Matplotlib).
- Good research experience/expertise and knowledge of research methods and techniques.
For informal enquiries, please contact the Project Lead, Dr. Khuong An Nguyen: K.A.Nguyen@brighton.ac.uk
The appointment is part-time (0.5 FTE) for a fixed term, finishing in June 2022.
It is planned that interviews will take place in mid-January 2022, and the successful candidate would need to be available to start in April 2022.
For full details of this post please see the attached job description.
Further details:
The University is committed to creating and maintaining an inclusive environment for all staff regardless of age, disability, family or caring responsibilities, gender identity, marital status, pregnancy or maternity, race, religion or belief (including non-belief), sex and sexual orientation. We embrace equality and diversity in our working, learning, research and teaching environment and are committed to maintaining a supportive and inclusive community. We particularly encourage applicants from Minority Ethnic backgrounds because the University is under-represented by Minority Ethnic staff.
For the vast majority of our roles, we operate an agile working system with time split between working on campus and at the employee's home. It is the University's expectation that home working will take place within the UK.
Further information about working for us, as well as the wide range of benefits we offer, can be found in the working with us section of our vacancies page.