Current Vacancies and Studentships

Research Fellow

Social Statistics & Demography

Location: Highfield Campus

Salary: £32,004 Full Time Fixed Term (Until 31/05/2021)

Closing Date: Friday 09 June 2017

Interview Date: To be confirmed

Reference: 869917CC

 

Bayesian Agent-Based Population Studies

This is an exciting opportunity to join a cutting-edge project “Bayesian Agent-based Population Studies (BAPS): Transforming Simulation Models of Human Migration”, funded by the European Research Council (http://cordis.europa.eu/project/rcn/209495_en.html).

The aim of BAPS is to develop a ground-breaking simulation model of international migration, based on a population of intelligent, cognitive agents, their social networks and institutions, all interacting with one another. In the modelling process, we will use Bayesian statistical principles to design innovative computer simulations, and to learn about the way the simulated individuals make decisions through cognitive experiments. In this way, BAPS will effectively integrate behavioural and social theory with modelling.

BAPS will be led by Dr Jakub Bijak, the Allianz European Demographer 2015, recognised as a leader in the field for methodological innovation, directing an interdisciplinary team with expertise in demography, agent-based models, statistical analysis of uncertainty, meta-cognition, and computer simulations.

You will have, or will be close to completing, a PhD* (or equivalent professional qualifications) with a strong statistical or mathematical component, such as in statistics, demography, economics, mathematics or computer science; detailed understanding and knowledge of Bayesian statistics; experience of statistical or computational modelling of demographic or other social processes; and proficiency in the use and programming of R or other equivalent statistical software. The ability to plan and organise work independently and as part of a team, and write research presentations and papers are also essential attributes. Experience of designing, implementing and analysing computational models of social processes (e.g. simulation-based models), and fitting models using Bayesian methods, will be an advantage.

You will perform the groundwork throughout the project, in particular collecting, organising and evaluating the available information, performing the modelling and experimental design analysis, drafting papers and presenting at conferences, as well as conducting organisational work related to dissemination events.

You will be based in the Department of Social Statistics and Demography, within the Social Sciences academic unit, Faculty of Social, Human and Mathematical Sciences, at the University of Southampton.  You will work closely with the project team: Dr Jakub Bijak (project lead, Social Sciences), Prof. Peter W F Smith (Social Sciences) and Prof. Jonathan J Forster (Mathematics), especially in relation to the statistical aspects of the work; and also with Dr Philip Higham (Psychology), and Prof. Adelinde Uhrmacher (Computer Science, University of Rostock), as well as with the two other research fellows on this project.  We also envisage maintaining close working relationships and information exchange with the ESRC Centre for Population Change, with the hub at the University of Southampton (www.cpc.ac.uk).

*Applications will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification.  The title of Research Fellow will be applied upon completion of PhD.  Prior to the qualification being awarded the title of Senior Research Assistant will be given.

Informal enquiries may be addressed to Dr Jakub Bijak, email: J.Bijak@southampton.ac.uk, telephone: +44 (0)23 8059 7486.

The position is tenable from 1 July 2017 or as soon as possible thereafter; not later than 1 October 

Application procedure:

You should submit your completed online application form at www.jobs.soton.ac.ukThe application deadline will be midnight on the closing date stated above. Please see the original job advertisement for further details.