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Research Fellow in Machine Learning for Space Physics
Astronomy Group
Location:
Highfield Campus
Salary:
£30,395
Full Time Fixed Term (12 Months)
Closing Date:
Friday 06 September 2019
Interview Date:
To be confirmed
Reference:
1170019WF
Postdoctoral position in Machine Learning for Space Physics
at the University of Southampton.
You will join the Astronomy group at the University of Southampton. The research
will involve application of machine learning techniques to classify magnetic
reconnection events in planetary magnetotails. The post is supervised by Dr.
Caitriona Jackman, and is funded through her fellowship of the Alan Turing
Institute, the national centre of excellence for data science and artificial
intelligence.
The post is funded for 12 months in the first instance due to funding restrictions
Candidates should have a *PhD or equivalent professional qualifications and experience in
space science, astronomy, computer science, or other closely related
discipline. Experience with machine learning and/or planetary magnetospheres is
highly desirable.
* Applications for Research Fellow positions will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification. The title of Research Fellow will be applied upon successful completion of the PhD. Prior to the qualification being awarded the title of Senior Research Assistant will be given.
For further details, please contact Dr. Caitriona Jackman via email c.jackman@soton.ac.uk or Tel: 02380 592048.
Application procedure:
You should submit your completed online application form at www.jobs.soton.ac.uk. The application deadline will be midnight on the closing date stated above. If you need any assistance, please call Charlene Tyson (Recruitment Team) on +44 (0) 23 8059 6803. Please quote reference 1170019WF on all correspondence.
Further details:
We aim to be an equal opportunities employer and welcome applications from all sections of the community. Please note that applications from agencies will not be accepted unless indicated in the job advert.