Radio Transients and Machine Learning
Lead Research Organisation:
University of Oxford
Department Name: Oxford Physics
Abstract
Alex Andersson will work on a project to look find, classify and investigate commensal field transients in radio data from the MeerKAT radio telescope. In the process he will develop machine learning techniques and work with citizen scientists via Zooniverse, developing techniques for combining human and machine classifications.
The work is motivated by the flood of new radio variables and transients being discovered in our data, and the need to develop new tools to maximise the scientific reward from their study. The MeerKAT data analysis and development of new tools for this and future radio telescopes aligns well with the UK's key strategic investment in the Square Kilometre Array, for which MeerKAT is one of two official precursors. Novel tools will be developed, and impact is potentially very high.
The work is motivated by the flood of new radio variables and transients being discovered in our data, and the need to develop new tools to maximise the scientific reward from their study. The MeerKAT data analysis and development of new tools for this and future radio telescopes aligns well with the UK's key strategic investment in the Square Kilometre Array, for which MeerKAT is one of two official precursors. Novel tools will be developed, and impact is potentially very high.
People |
ORCID iD |
Rob Fender (Primary Supervisor) | |
Alexander Andersson (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ST/V506953/1 | 30/09/2020 | 29/09/2024 | |||
2443927 | Studentship | ST/V506953/1 | 30/09/2020 | 31/03/2024 | Alexander Andersson |