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Research Assistant/Associate (Fixed Term)


Fixed-term: The funds for this post are available for 2 years in the first instance.

This is an exciting opportunity for an ambitious data scientist to work within the LSST programme at the Institute of Astronomy, (West Cambridge).

LSST will transform observational astrophysics. The 8.4m telescope set to commence full science operations in 2022, will survey the visible sky every few nights in six optical bands to address four key science themes: Constraining the nature of dark energy and dark matter, making an inventory of small moving bodies in the Solar System, exploring the transient optical sky, and determining the accretion history of the Milky Way.

The IoA is involved in the LSST:UK programme, contributing to the development of effective algorithms supporting LSST Milky Way galactic structure science. Specifically, the IoA is currently developing algorithms to improve both the discrimination between stars and galaxies in the deep multi-colour LSST data and automate the detection of tidal stream structure in the image data. The successful candidate will interface with the 'STREAMS' group led by Dr Belokurov, interact with the Cambridge Astronomical Survey Unit and the Cambridge Gaia Group, and be able to fully participate in the LSST collaboration.

The successful candidate will be responsible for contributing to the scientific development of LSST related analysis algorithms. The position will also involve: liaising with the LSST project team and other science users; and collaborating on research programs exploiting early access to LSST and related surveys.

Applicants must have a Ph.D. in astronomy, and have a strong computing and programming background. Previous experience in large-scale imaging surveys would be advantageous. Candidates are expected to be familiar with the acquisition and reduction of data from astronomical surveys, use of machine learning techniques applied to big data, and with the use of database systems. Experience and practical knowledge of the Python language is a requirement, while knowledge of SQL and database systems would be advantageous.

Salary will be £25,298 - £29,301 (Research Assistant) or £29,301 - £38,183 (Research Associate) depending on experience and qualifications. The position is tenable initially for a fixed term period of 24 months with prospects for further extension.

Starting Date: From 1st September 2017 or as early as possible thereafter.

We welcome applications from individuals who wish to be considered for part-time working or other flexible working arrangements

To apply online for this vacancy, please click on the 'Apply' button below. This will route you to the University's Web Recruitment System, where you will need to register an account (if you have not already) and log in before completing the online application form.

Please ensure that you upload your Curriculum Vitae (CV), research statement, publication record and covering letter. Please submit your application by midnight of the closing date of 30th June 2017. The names and contact details of three referees are a necessary part of the submission. Referees of short-listed candidates will be contacted and asked to provide a reference before the interview date.

If you have any queries about your application, please contact Ms Joy McSharry by email jpm(at)ast.cam.ac.uk.

Further information can be obtained from Dr Vasily Belokurov (vasily(at)ast.cam.ac.uk) or Professor Richard McMahon (rgm(at)ast.cam.ac.uk).

Please quote reference LG12177 on your application and in any correspondence about this vacancy.

The IoA is committed to providing a family friendly environment for researchers and is ensuring that should parental leave be needed during the course of employment, there is provision for extension to contract to compensate for the parental leave taken.

The University values diversity and is committed to equality of opportunity.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

Further information

Apply online