Post-doctoral positions in Data Mining for Socio-Economic Systems (2 pos)
The positions are meant for quantitative researchers in Data Mining of unstructured data sources and in Text Mining. In particular, successful candidates will develop methods to perform Analytical Web Crawling, Scraping, Web Search and Information Retrieval with the aim of building and analyzing sensible datasets to now cast the state of the whole economy or of a specific sector. The hired postdocs will also make use of Text Mining, Sentiment Analysis, and Opinion Mining techniques to extract and analyze information from texts and social media to sense the perceived state of the economy and to enrich the now casting analysis.
Knowledge of and, possibly, working experience in Data Mining and Machine Learning are required. Knowledge of Text Mining 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 Economics, Physics, Computer Science, Computer Engineering, Mathematical 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 in Web Crawling and Information Retrieval
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