SHARE, the Survey of Health, Ageing and Retirement in Europe, is looking for a Country Team Lead. Read more about the position and the application procedure here.
In May 2023, the ODISSEI Social Data Science Team (SoDa) hosted a workshop on causal impact assessment. The workshop materials are now available online.
Read more here.
Research software is widely used by researchers from all fields. Research software represents the set of operations and instructions to shape raw data to analytical and computational purposes. In this blog post, we describe how the FAIR principles apply to research software and point to useful resources.
The European Social Survey (ESS) is looking for a national coordinator. Lees hier meer over de positie en de sollicitatieprocedure.
ODISSEI welcomes proposals for presentations on computational social science to be given at its conference on 2 November 2023 in Utrecht.
First Aid for Data Questions: How the SoDa team empowers interdisciplinary scientists with computational methods
The ODISSEI SoDa team helps researchers develop tools for their research. Political Scientist Ruth Carlitz approached them to discuss how computational methods such as machine learning and large-scale text analysis could help her extract information from foreign aid project evaluations.
On 25 May, from 14:00-15:00, ODISSEI and Centerdata organize an online information event for the LISS panel grant call that opens up this spring.
On 9 May, from 12:00-13:00, ODISSEI is organizing an information session on how the national infrastructure can support researchers in their upcoming ERC or NWO funding application.
This project uses nationwide individual-level register data from the Netherlands to study the relationship between problematic debts and mental health. The researchers use the OSSC to run the algorithm on millions of observations.
This project aims to develop a synthetic data generator framework using artificial intelligence technologies while concurrently exploring ethical-legal perspectives in the trade-off between data privacy and the potential utilization of synthetic representations. The project uses a fully data-driven method and the ODISSEI Secure Supercomputer to conduct computationally expensive experiments.