Are you interested in developing advanced statistical models? And would you like to open the way for new forms of real-time mood sensing going forward? The department of Methodology and Statistics has a job opening for a PhD candidate, interested in developing advanced statistical models to detect episodes of depression in real-time.

Your job
The project is a close collaboration between the department of Methodology and Statistics and the department of Youth and Family. Depression prevalence in emerging adults is alarmingly high. To advance clinical care for this at-risk population, we need to exploit technological advances such as smartphones and wearables to move beyond the current univariate and time-static standards. Smartphones and wearable devices facilitate densely spaced longitudinal measurements, enabling the study and monitoring of behaviour and mood dynamics unfolding over time. Pairing novel statistical models with these dense measurements presents the unique opportunity to unveil the nature and temporal structures of emerging adults’ affective, behavioural and social experience in depressed mood at a personalised level, which can be exploited for prediction.

You will develop and validate a probabilistic unsupervised learning method, which utilises deep phenotyping data to anticipate increases in psychopathological symptoms in real-time. The ideal statistical method:

1. accommodates the latent and multivariate property of mood;
2. characterises mood in a set of distinct, mutually exclusive latent states;
3. obtains the dynamics between the latent mood states over time;
4. adopts a personalized approach; and
5. explicitly and accurately models the durations of the latent mood states.

The extended (multilevel) hidden Markov model ticks all above boxes and will be used as our starting point. You will implement the developed algorithm in a statical package within the open statistical software environment R. To validate the model, you will conduct an extensive simulation study on the estimation and prediction performance of the developed algorithm. In addition, you will set up a study to obtain an extensive longitudinal (6-weeks, 5-daily) deep phenotyping dataset on multiple affective and behavioural experiences previously associated with depressed mood. By combining the obtained deep phenotyping data with the developed personalised depression prediction algorithm, you can derive empirically derived depressive-mood states that reflect the multidimensional complexity of depression, examine the dynamics over time in depressed mood, infer personalised model parameters, and set a first step towards real-time personalised prediction of depressed mood episodes.

The position also includes between 10% and 20% teaching tasks at the department of Methodology and Statistics of the faculty of Social and Behavioural Sciences.

We are looking for an enthusiastic colleague who meets the requirements below:

• a Master’s degree in Methodology and Statistics or a related field at the start of the position;
• strong programming skills in R;
• affinity (and preferably experience) with intense longitudinal data and/or hidden Markov models;
• excellent verbal and written communication skills in English;
• a motivated and collaborative team member, who is communicative and open for collaboration across scientific fields;
• is able to meet deadlines, and conduct research independently as well as part of a team.

We offer:

• a position for one year, with an extension to 4-4,5 years (depending on amount of teaching) upon positive evaluation;
• a working week of 32 - 40 hours and a full-time gross salary between €2,770 in the first year and €3,539 in the fourth year of employment (scale P of the Collective Labour Agreement Dutch Universities (CAO));
• 8% holiday bonus and 8.3% end-of-year bonus;
• a pension scheme, partially paid parental leave, and flexible employment conditions based on the CAO.

In addition to the employment conditions from the CAO for Dutch Universities, Utrecht University has a number of its own arrangements. These include agreements on professional development, leave arrangements, sports and cultural schemes and you get discounts on software and other IT products. We also give you the opportunity to expand your terms of employment through the Employment Conditions Selection Model. This is how we encourage you to grow. For more information, please visit working at Utrecht University.

Universiteit Utrecht

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 Pathways to Sustainability. Shaping science, sharing tomorrow.

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.

You will be employed at the Department of Methodology and Statistics of the Faculty of Social and Behavioural Sciences. The research of the Department of Methodology and Statistics focuses on a broad array of methods and techniques for the social and behavioural sciences and comprises topics like: longitudinal studies, multilevel analyses, collection and analysis of intensive big data, survey research, research synthesis techniques, best practices when doing research, and qualitative research and mixed methods research. In addition, the Department of Methodology & Statistics provides teaching in methods and statistics within all Bachelor’s and Master’s degree programmes of the Faculty of Social and Behavioural Sciences and University College Utrecht. The department also advises staff and students with respect to their research activities. You will find a dynamic and pleasant working environment, in a group that is actively involved in scientific research at the highest international level. In addition, you will become a member of the Interuniversity Graduate School of Psychometrics and Sociometrics. The supervisory team will include Dr Emmeke Aarts (Department of Methodology and Statistics) and Dr Bill Hale (Department of Youth and Family).