As part of my recently awarded ESRC “Future Research Leaders” grant I am recruiting a researcher assistant/ associate to work with me on the analysis and visualisation of the latest big and open social science datasets. I am after someone who is passionate about (spatial) data and who has the computing skills/ background to work with it. Click here to apply.

I have pasted some further details below:

Research Associate BODMAS project

Department: The Bartlett Centre for Advanced Spatial Analysis (CASA)

Reports to: Dr James Cheshire

Grade: Grade 7 £32,375 or Grade 6B £28,338 where the successful candidate does not hold a PhD;  [inc London Allowance of £2,834 pa].

Funding duration: 18 months

Closing date: 25th September 2013

Interview date: First week of October 2013

The Bartlett Centre for Advanced Spatial Analysis (CASA) develops and researches emerging computer technologies in several disciplines that deal with geography, space, location, visualisation, and the built environment. CASA’s focus is to be at the forefront of what is one of the grand challenges of 21^st Century science: to build a science of cities from a multidisciplinary base, drawing on cutting edge methods, and ideas in modelling, complexity, visualisation and computation. Our current mix of architects, geographers, mathematicians, physicists, archaeologists and computer scientists make CASA a unique and world-leading unit within the Faculty of the Built Environment at UCL. For more information about CASA, please visit http://www.bartlett.ucl.ac.uk/casa

 

The Role

 

We are seeking a highly-motivated individual with an interest in open data who is experienced in working with large spatially referenced databases. They will be able to undertake complex data analysis using programming languages such as Java, Python and R, and be able to communicate their results through the production of maps and other visualisations. We welcome applicants with a PhD or top-graded masters qualification in a relevant field (see below) and are keen to recruit someone actively working with open data.

 

The successful candidate will work closely with Dr. James Cheshire, the project lead, and become an integral part of CASA’s research community. The project has a range of partners including the Open Data Institute, ESRI (UK) and the University of Illinois.

 

Big, Open Data: Mining and Synthesis (BODMAS)

 

The volume and assortment of available data for research in the social sciences has dramatically increased in recent years- a trend that shows no sign of stopping. For the first time researchers can obtain large amounts of population data free of charge (so-called “open data”) thanks to government websites such as data.gov.uk. When these data are combined with the computing power to perform complex calculations it creates an unprecedented opportunity for social science researchers. We are now in an era of big data and this is fundamentally changing the research environment for investigations across social science. The purpose of this project is to develop some of the new perspectives required to adapt to these changes in the practice of data modeling and synthesis.

 

These new perspectives include the need to account for the increased uncertainty in data provenance and less thorough metadata, as the data provision philosophy has shifted away from careful collection and dissemination to an emphasis on expediency. Researchers increasingly have to temper gains in data volume against losses in data quality when they embark on a study. Extra caution is also required when combining datasets, especially if they contain geographic information, as it is not always case that the spatial scales are compatible. The proposed project will develop a web-based tool to help social scientists minimise or eradicate these issues by enabling the synthesis, mining and visualisation of open datasets in a more informed way. The project will also use the newly combined data to undertake more complex analyses of population processes using supercomputers to gain unprecedented insights into social phenomena.

 

Key to the success of this project is a research assistant/associate who can apply their programming and data manipulation skills to tackle the challenges of open data to create meaningful data products and engaging data visualisations.