Postdoc on Incomplete Data Science (1.0 FTE)

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Postdoc on Incomplete Data Science (1.0 FTE)

Job description

The mice team at Utrecht University seeks an excellent postdoctoral researcher to enhance our strength in methodological research and development of open software. The successful candidate will be a member of the mice research and development team and work with topics related to incomplete data analysis and machine learning, with an interest in applications to the social, behavioural, biomedical, and clinical sciences.
This position is funded by NWO Open Competition XS Mindless Mice: Multiple imputation without explicit model specification (406.XS.01.104). The missing data group at Utrecht University is strongly integrated with the Utrecht Focus Area Applied Data Science and has excellent connections to social sciences, health sciences and official statistics. Beside collaborations within this larger project and the missing data team at the department of methodology and statistics led by prof. dr. Stef van Buuren and dr. Gerko Vink , 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:

  • incomplete data theory;
  • causal inference / probabilistic graphical models;
  • machine learning;
  • data synthesis;
  • differential privacy;
  • explainable AI;
  • differentiable programming.

Contributions to FOSS software projects and other open science practices are explicitly appreciated in our group.
The tasks include:

  • developing data-driven automated techniques for solving incomplete data problems that minimizes the need for user intervention;
  • building own research related to by publishing excellent research (research products may include papers as well as FOSS software, outreach, etc.);
  • collaborating on the NWO Open Competition project;
  • contributing 20% of the time to teaching at the Methodology and Statistics department , for example within the new UU Master’s and minors in Applied Data Science, or through supervision of Master's students.
  • assisting in training and supervision of PhD candidates and Master's students;
  • contributing to the missing data group group activities, such as the development and research meetings.


We look for a motivated and highly skilled candidate with:

  • a PhD degree in statisics, computer science, computational social sciences, or any related or relevant field;
  • excellent development and programming skills in R;
  • excellent communication skills in English;
  • creativity, independence and dedication to advancing (open) science;
  • a research vision and a will to develop it in an environment with a large degree of academic freedom;
  • ability and will to collaborate and work in teams;
  • excellent social skills;
  • ability and will to do research on one (or more) of the topics of interest of the research group;
  • ability and will to support teaching and/or to (co-)supervise master and PhD candidates (this position includes both research and education responsibilities which are aimed at supporting our tasks and at developing the postdoc’s skills).


We offer a temporary position (1,0 FTE) for a period of 10 months in an international working environment. The gross salary - depending on previous qualifications and experience - ranges between €2,960 and €5,439 (scale 10 or 11 according to the Collective Labour Agreement Dutch Universities) per month for a full-time employment. Salaries are supplemented with a holiday bonus of 8% and a year-end bonus of 8.3% per year.
In addition, Utrecht University offers excellent secondary conditions , including an attractive retirement scheme, (partly paid) parental leave and flexible employment conditions (multiple choice model). For more information, please visit working at Utrecht University .

About the organization

A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University , the various disciplines collaborate intensively towards major strategic themes . Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Sustainability.
The Faculty of Social and Behavioural Sciences is one of the leading faculties in Europe providing research and academic teaching in cultural anthropology, educational sciences, interdisciplinary social science, pedagogical sciences, psychology, and sociology. Almost 7,000 students are enrolled in a broad range of undergraduate and graduate programmes. The Faculty of Social and Behavioural Sciences has some 1,100 faculty and staff members, all providing their individual contribution to the training and education of young talent and to the research into and finding solutions for scientific and societal issues.
The faculty attaches great importance to the fact that its employees can be widely deployed in the university organization, now and in the future, to further professionalize the support of education and research. To encourage this, every employee is given the time and facilities – for example in the form of training – at some point in their career to participate in projects or work in other departments. Characteristics that the faculty considers important are involvement, the ability to collaborate and flexibility. The faculty is located at Utrecht Science Park near the historical city centre of Utrecht.
The MICE (Multivariate Imputation by Chained Equations) team at Utrecht develops methodology and software aimed at solving incomplete data and synthetic data problems. The MICE  package implements a method to deal with missing data. The package creates multiple imputations (replacement values) for multivariate missing data. The method is based on Fully Conditional Specification, where each incomplete variable is imputed by a separate model. The MICE algorithm can impute mixes of continuous, binary, unordered categorical and ordered categorical data. In addition, MICE can impute continuous two-level data, and maintain consistency between imputations by means of passive imputation. Many diagnostic plots are implemented to inspect the quality of the imputations.
The increasing use of data driven analysis techniques in data science & AI requires a great deal of expert knowledge. When the data are incomplete, this knowledge must also include the exact specification of statistical imputation models to solve for the missingness. The Mindless Mice project proposes mindless imputation, a data-driven automated technique for solving incomplete data problems that minimizes the need for user intervention. With mindless imputation, applied researchers can focus on the analysis, knowing that the used imputation technique allows for valid inferences and reliable predictions in the context of incomplete data.
The Utrecht focus areas link fundamental research to a social mission. They are testing grounds in which we focus on a theme, take new paths and enter into new partnerships. The focus area Applied Data Science  builds a community of researchers who are interested in developing the field of data science. By joining forces and working interdisciplinarily, we can accelerate the development of data science techniques within Utrecht University. This includes introducing data science techniques in research areas where they are not yet applied.

Additional information

For more information about this position, please contact Kevin van Kats (Department manager) via .
Are you an international applicant? Our International Service Desk can answer your questions about living in the Netherlands as international staff .


Everyone deserves to feel at home at our university. We welcome employees with a wide variety of backgrounds and perspectives. 
To apply, please send the following documents via the ‘apply’ button:

  • a one-page personal research statement, including motivation to work within our group;
  • your curriculum vitae, including a list of your publications and/or other research or software development outputs;
  • the contact information of two references.

If you know someone who is suitable for this position, please share the vacancy.

The application deadline is
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