Postdoc in Statistics

The attention to LGBTQ+ people’s rights has clearly progressed. However, there are still evident negative attitudes towards LGBTQ+ showing important regional differences. Unfortunately, national level sample surveys are not designed to produce reliable regional estimates of those phenomena. Therefore, small area estimation (SAE) methods are used. With technological advances, Big Data now offers valuable spatial insights to predict such attitudes. This project investigates drawbacks and potentials of Big Data in SAE to measure attitudes towards LGBTQ+.

Your job
The Department of Methodology & Statistics invites applications for a fixed-term research position in statistics and data science, as part of the NWO (Dutch Research Council) project “Digital Behavioural Data to Enhance the Quality of Regional Estimates of Attitudes towards LGBTQ+ People”, led by Dr Angelo Moretti and Dr Camilla Salvatore.

This project aims to shed light on the use of big data, in particular data obtained via OpenStreetMap and Google Trends, as auxiliary information to enhance small area estimates of attitudes towards LGBTQ+ communities in Europe. We consider the following research questions (RQ): RQ1: which variables obtained from big data may help to provide better quality estimates compared to variables obtained from traditional data sources? RQ2: how can we combine the two different data sources in area-level models to measure attitudes towards LGBTQ+ people? RQ3: when both traditional and non-traditional data sources are used as auxiliary information, do we need to apply statistical approaches to correct for selectivity and coverage errors?

In the position you are responsible for:

1. Looking for potential data sources and identify their advantages and disadvantages within sub-national analyses
2. Identifying measurements errors and selectivity issues arising from those data sources and formulate modelling strategies on how to take into account for those
3. Estimate small area models and produce maps after assessing modelling results
4. Produce Open Source R software
5. Writing reports and research articles where you will be co-author.

You hold a PhD (or are close to submission, or have recently submitted) in statistics, data science, or a related field.
You have a strong statistical background.
We are looking for you if you have:

• Proficiency in written and spoken English (required)
• Solid expertise in statistical modelling
• Advanced R skills

Your suitability is ideally demonstrated by:

• Expertise in survey statistics and methodology
• Experience with data integration methods
• Knowledge of small area estimation

• a job for six months (if you hold a PhD);
• a working week of 36 - 40 hours and a gross monthly salary of € 4,227 in the case of full-time employment (salary scale 10.5 under the Collective Labour Agreement for Dutch Universities (CAO NU);
• a job for seven months (if you don't hold a PhD yet)
• a working week of 36 - 40 hours and a gross monthly salary of € 4,060 in the case of full-time employment (salary scale 9.3 under the Collective Labour Agreement for Dutch Universities (CAO NU) (if you don't hold a PhD yet);
• 8% holiday pay and 8.3% year-end bonus;
• a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.

In addition to the terms of employment laid down in the CAO NU, Utrecht University has a number of schemes and facilities of its own for employees. This includes schemes facilitating professional development, leave schemes and schemes for sports and cultural activities, as well as discounts on software and other IT products. We also offer access to additional employee benefits through our Terms of Employment Options Model. In this way, we encourage our employees to continue to invest in their growth. For more information, please visit Working at Utrecht University.

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