We are seeking a Post Doctoral Researcher to join an international project on the
development of methods for analysis and visualization of ‘big data’ from computational agent-based models (ABMs) of coupled human-natural systems.
This vacancy is part of a multidisciplinary multinational MIRACLE project (MIning
Relationships Among variables in large datasets from CompLEx systems). MIRACLE is a joint project between the Center for Social Dynamics & Complexity at the Arizona State University (USA), Centre for Environmental Change and Human Resilience at the University of Dundee and the James Hutton Institute (UK), Waterloo Institute for Complexity and Innovation at the University of Waterloo (Canada), and the Centre for Studies in Technology&Sustainable Development and the department of Geo-information Processing at the University of Twente (NL). The bottom-up structure of ABMs enables simulation and investigation of complex systems and their emergent behavior with a high level of detail; however the stochastic nature
and potential combinations of parameters of such models create large non-linear
multidimensional ‘big data’, which are difficult to analyze using traditional statistical methods.
Our project addresses this challenge by developing algorithms and web-based analysis and visualization tools that provide automated means of discovering complex relationships among ‘big’ output data of social science ABMs fitted with empirical data.
The Post Doctoral Researcher will (i) perform multiple model runs of the spatial ABM of a housing market under various parameter settings, (ii) mine, analyze, and synthesize large-scale model output data, and (iii) collect and extend methods for statistical analysis and visualization of non-linear, discontinuous and often power-law distributed data from spatial ABMs of this and other complex socio-ecological systems. In addition a close cooperation with the Canadian, US and UK project partners on the development of web-based facilities for interactive visualization and analysis of archives of ABMs output data is anticipated.
The Post Doctoral Researcher will be appointed at the Centre for Studies in Technology and Sustainable Development (CSTM) at the School of Management and Governance (SMG).
There will be close cooperation with the Department of Geoinformation Processing (GIP) at The Faculty of Geo-Information Science and Earth Observation (ITC). Work will be conducted in close cooperation with the Canadian, US and UK project partners.
Requirements
A candidate should ideally:
• hold (or very soon receive) a PhD degree in Computer Science, Mathematics,
Complex Systems, Spatial and/or Agent-based modeling;
• have strong quantitative skills and ability to program in Java, C++, Netlogo or other programming language/platform;
• have good knowledge of statistics and know R package;
• demonstrate fluent written and spoken English skills;
• have independent research and publication skills;
• good spatial modeling skills, familiarity with housing markets, and/or GIS is an
advantage.
Conditions of employment
This is a full-time position of a PostDoctoral researcher for a period of 1.5 years. Extension possible if other relevant projects are funded. The gross monthly salary will increase from €2919,- in the first year to € 3831,- in the final year (in accordance with the Collective Labour Agreement for Dutch Universities) plus a holiday allowance (8%), and end-year bonus (8.3% of the annual salary). In addition, the University of Twente offers additional attractive employment conditions and benefits.
Starting date: by arrangement in April – May 2014. First reviews and interviews will start on March 28th 2014.
Information and application
For more information on this position please contact Dr. A. Voinov ([email protected] ) and Dr. T.Filatova ([email protected]).
To apply for this position, please fill in the online application form http://www.utwente.nl/ vacatures/en/ Please attach your (1) cover letter, (2) resume, (3) names and contact information of at least 3 referees, and (4) list of publications.