Post-doctoral positions in Data Science for the Analysis of Socio-Economic Systems (2 position
The positions are meant for quantitative researchers capable of performing statistical modeling and analysis of socio-economic micro data (large size, high dimensionality) using tools of machine learning, complex network theory and/or advanced statistical techniques for the analysis of high dimensional data.
Knowledge of and possibly working experience in mathematical statistics, complex network analysis, both theoretical and applied, are required. Knowledge of statistical mechanics is a plus, but not strictly required.
Successful candidates will work in a multidisciplinary research group consisting of computer scientists, economists, applied mathematicians, statisticians, physicists, and data scientists in a cutting-edge research environment and will play a key role in developing predictive analytic tools and statistical methods in economics and finance and in producing high-impact publications.
- PhD in Physics, Economics, Mathematics (including Financial or Applied Math), Mathematical Engineering, Computer Science, Computer Engineering, Statistics, or related disciplines
- A strong record in research productivity
- Fluency in written and oral English
- Excellent written and oral presentation skills
While not mandatory, the following qualifications are strongly desired:
- Previous experience with data science projects, preferably in economics, finance, and social sciences
- Experience in working with complex networks theory
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