Research Associate in IMAXT Imaging Data Science

Submission Information
Publish Date: 
Sunday, February 23, 2020
Archive Date: 
Sunday, March 29, 2020
Job Summary
Job Category: 
Post-doctoral Positions and Fellowships
Institution Classification/Type: 
Foreign
Institution/Company: 
University of Cambridge
Department Name: 
Institute of Astronomy
City: 
Cambridge
State/Province: 
Cambridgeshire
Zip/Postal: 
CB3 0HA
Country: 
United Kingdom of Great Britain and Northern Ireland
Announcement
Job Announcement Text: 

Fixed-term: The funds for this post are available until 30 April 2023 in the first instance.

This is an exciting opportunity for an ambitious applications data scientist to work within the Cambridge Astronomical Survey Unit (CASU) at the Institute of Astronomy (IoA) at West Cambridge site as part of the IMAXT Cancer Research UK Grand Challenge Project Team. The post is located at the Institute of Astronomy, but the successful candidate will be expected to spend considerable time at the IMAXT project team office at Cambridge Institute, Cancer Research UK, Cambridge, situated on the Addenbrooke's Biomedical Campus in Cambridge (West Cambridge).

The Imaging and Molecular Annotation of Xenografts (IMAXT) project is taking an integrated approach in producing faithful three-dimensional maps of tumours and their host environment, wherein each cell is identified and molecularly annotated. These maps will be accessed in an interactive, virtual reality framework. This will provide an entirely new way for scientists and physicians to understand how cancer develops and predict its clinical behaviour.

CASU undertakes a range of activities in wide field astronomy including: developing and operating pipeline processing and analysis systems for optical and near-infrared mosaic imaging and spectroscopic surveys; together with various space mission projects including PLATO and Euclid, and manages a data processing and archive centre.

Within IMAXT, CASU is responsible for developing high throughput pipelines to segment and align the various IMAXT imaging datasets. CASU is also managing the flow of reduced data, both images and catalogues into the central IMAXT database, and defines the structure of this database.

You will work within the CASU-IMAXT team and be responsible for contributing to the development of novel scientific algorithms and applications in the areas of image analysis and data mining of the catalogues extracted as an output of the image analysis of IMAXT data. The role will involve: contributions to the supporting computational infrastructure; liaising with the IMAXT project teams and external science users; contributing to documentation and user manuals; and collaborating in the IMAXT research programs to optimise interpretation and use of such IMAXT data.

A good practical knowledge of scientific algorithm development and either a PhD in a numerate discipline (preferably Astronomy, Physics, Computer Science, Computer Engineering or related field) or a Masters level qualification plus relevant experience is required. You should have knowledge of Python and C/C++, and experience in image analysis and machine learning. Experience with database (SQL) and web-based systems is desirable. The ability to work as part of a team and have good communication skills is also required.

Candidates with experience of working in a research environment involving scientific processing of medical or astronomical image data are particularly welcomed

Please submit your application by midnight of the closing date of Sunday, 29th March 2020. If you have any queries about your application please contact Ms Joy McSharry (jpm(at)ast.cam.ac.uk). Further information can be obtained from Dr Nicholas Walton (naw(at)ast.cam.ac.uk).

Included Benefits: 

Employee benefits  http://www.jobs.cam.ac.uk/offer/

Application Deadline: 
Sunday, March 29, 2020
Current Status of Position: 
No Status Given (Opted Out)
Apply to Job
Attention To: 
Dr Nicholas Walton
Inquiries About Job
Attention To: 
Ms Joy McSharry
Subject: 
LG22557
Email: 
jpm(at)ast.cam.ac.uk