The Human Data Science Group at Utrecht University seeks an excellent Postdoctoral Researcher to enhance our strengths in methodological research on the interface of statistics, data science, and computational social science.
The successful candidate will work with topics related to (multimodal) machine learning, with an interest in applications to the social, behavioural, biomedical, and clinical sciences. We are particularly interested in models to deal with bias in human generated data, including measurement bias, invalidity, selection bias, and fairness.
This position is funded by NWO vidi project Advancing social science with valid measures derived from incidental data (VI.Vidi.195.152). The group is strongly integrated with the Utrecht focus area Applied Data Science and the new program Utrecht Data Science for Health. Beside collaborations within this larger project and the human data science group at the Department of Methodology and Statistics headed by Dr Daniel Oberski, there will be ample opportunities to collaborate with multiple researchers within and outside of the university.
Research topics of interest include, but are by no means limited to:
- latent variable modeling, (deep) representation learning;
- computational statistics;
- multimodal learning, including NLP;
- differential privacy;
- fair ML;
- probabilistic graphical models/causal modeling;
- differentiable programming.
Contributions to FOSS software projects and other open science practices are explicitly appreciated in our group.
Tasks and responsibilities include:
- development of own research line by publishing excellent research (research products may include papers as well as FOSS software, outreach, etc.);
- collaborate on NWO vidi project;
- assist in training and supervision of PhDs;
- seek collaboration with (inter)national partners;
- contribute to Human Data Science Group activities, such as Methodology & Statistics Data Science Lab (MSDSlab), reading groups etc.;
- contribute 10% of time to teaching at department, for example within the new Utrecht University Master’s and minors in Applied Data Science, or through supervision of Master's students.