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Data Validation Scientist (CU9/IoA) (Fixed Term)

University of Cambridge - Institute of Astronomy

Location: Cambridge
Salary: £29,605 to £44,263 per annum
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 24th January 2024
Closes: 23rd February 2024
Job Ref: LG40175

Fixed-term: The funds for this post are available until 31 March 2026 in the first instance.

This is an interesting opportunity for a data scientist to work at the Institute of Astronomy, University of Cambridge, as part of the Gaia and PLATO system development teams within the IoA Data Projects (CamCEAD) group.

Gaia is a space observatory of the European Space Agency (ESA), launched in 2013, operational until 2025 and a final data release 2030/31. Gaia's key objective is a detailed study of the Milky Way, revealing our Galaxy's content, dynamics, current state and formation history. The IoA is responsible for development and operation of the (spectro)-photometric processing system. PLATO is an ESA mission, that will detect and characterise a significant sample of exoplanets around bright stars. Within the PLATO Consortium, the IoA team is responsible for development and operation of the Exoplanet Analysis System, enabling detection of the signatures of exoplanets from high-precision photometric light curves of host stars.

The successful candidate will work initially within the Gaia software development team, with likely later involvement in PLATO development. Main tasks will be in photometric light curve analysis and validation (Gaia and PLATO) and data analysis and development of novel scientific algorithms and applications in areas of photometric and spectrophotometric processing (Gaia). The role will involve liaising with wider mission consortium teams and external science users; contributing to documentation; and collaborating in Gaia and PLATO stellar and exoplanet related research programs to optimise interpretation and use of such mission data. The role will include interactions with the wider CamCEAD team, with potential to contribute machine learning expertise in the context of data systems ranging from ground-based spectroscopy (e.g. WEAVE) to medical imaging (i.e. IMAXT).

The successful candidate will have experience in astronomical data analysis activities, coupled with use of machine learning approaches to data validation, good practical knowledge of scientific algorithm development and a PhD degree in a numerate discipline (preferably Astronomy, Physics, Computer Science, Computer Engineering or related field).

Candidates are expected to be familiar with acquisition and reduction of data from large-scale astronomical facilities or surveys and with use of database and web-based systems. Knowledge of Python/Java and object-oriented programming is required; knowledge of database systems would be advantageous.

The ability to work as part of a team and good communication skills are required. The post-holder will be required to attend meetings elsewhere in the UK and overseas.

Salary will be on the Research Associate scale. A successful candidate with a PhD will be appointed at Grade 7 (£36,024 to £44,263 per annum). A candidate not yet awarded their PhD will initially be appointed at Grade 5 (Research Assistant - £32,982 to £33,966 per annum) and, upon award of PhD, promoted to Grade 7.

To apply online for this vacancy and to view further information, please click the 'Apply' button above.

Shortlisted candidates will be interviewed online, w/c 11 March 2024.

Please quote reference LG40175 on your application and related correspondence.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. Applications from underrepresented groups are particularly welcome.

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

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