Postdoc Human Data Science (1.0 FTE)

Hours per week: 
38 to 40
Faculty: 
Faculty of Social and Behavioural Sciences
Department: 
Methoden en Technieken
Application deadline: 
7 March 2020

Job description

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.

Qualifications

We are looking for a motivated and highly skilled candidate with:

  • a PhD degree in Computer Science, Computational Statistics, or any related field;
  • excellent communication skills in English (there is no requirement to learn Dutch);
  • creativity, independence and dedication to advancing (open) science;
  • research vision and 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's and PhD students (this position includes both research and education responsibilities, aimed at supporting our tasks and developing the Postdoc’s skills).

Offer

We offer a position (1.0 FTE) for a period of two years. The gross salary - depending on previous qualifications and experience  - ranges between €2,709 and €4,978 (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). More information about working at Utrecht University can be found here.

About the organisation

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 applied yet.

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 societal themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Sustainability.

Utrecht is a young and vibrant city with a large academic population, around 30 minutes south of Amsterdam. It combines a beautiful old city centre with a modern university. Utrecht has an excellent quality of life, with plenty of green space and a strong bicycle culture.

The Faculty of Social and Behavioural Sciences is one of the leading Faculties in Europe providing research and academic teaching in Interdisciplinary Social Science, Cultural Anthropology, Educational Sciences, Pedagogical Sciences, Psychology, and Sociology. More than 5,600 students are enrolled in a broad range of undergraduate and graduate programmes. The faculty has about 850 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.

Additional information

Additional information regarding this position can be obtained by contacting Kevin van Kats (Department Manager) via K.vanKats@uu.nl.

Apply

If you would like to apply, please send us your application by using the 'apply’ button below. Your application must include:

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

The application deadline is 7 March 2020.