This recently funded five-year ERC Project has the goal to build the early warning system WARN-D to reliably predict depression in young adults before it occurs. We will follow 2,000 young adults over two years, and integrate emerging theoretical, measurement, and modelling approaches from different scientific fields. Depression will be conceptualized as a complex, dynamical, biopsychosocial system in which causal relations between a host of variables can move the system from a healthy to a clinical state, consistent with the Network Approach to Psychopathology that Dr. Fried co-developed. In addition to traditional mental health surveys every few months, we will assess how young adults are doing in their daily lives for three months, collecting smart-phone based ecological momentary assessment (EMA) data and smart-watch based digital phenotype data. This will provide insights into temporal patterns of mood, symptoms, sleep, and activity. Dynamical network models will be used to study the within-person mood systems, and machine learning models to build WARN-D. The team for this project will consist of the two PhD positions announced here; a postdoctoral researcher who will focus on building WARN-D; bachelor and master students; and Eiko Fried.

PhD position 1: Mapping the human mood system
The first project is focused on describing and understanding the biopsychosocial mood system. Specific goals will be 1) to map out the mood systems of all participants by combining EMA data, digital phenotype data, and dynamic network models; 2) to investigate inter-individual differences of mood systems across participants; and 3) to model the temporal stability of mood systems within participants.

PhD position 2: Early warning signals for depression onset
The second project is focused on participants that transition into depression during. Specific goals will be 1) to investigate two early warning signals from field of complexity science, connectivity and critical slowing down; 2) to test whether prodromal depression data hold signals to forecast depression; and 3) to investigate whether depression onset is categorical (i.e. abrupt) or dimensional (i.e. gradual).

Key responsibilities
This ERC grant is situated between clinical psychology, statistical methodology, and complexity sciences. The activities of both positions include:

• Active participation in the organization of the study as well as data collection;
• Reading into and keeping up with developments in the relevant fields;
• Data analysis;
• Preparing research for publication;
• Presenting work at internal (seminars) and external (conferences);
• Working collaboratively to achieve joint research projects;
• Supervision of bachelor and master students.

• Master’s degree and excellent track record in Clinical Psychology, Quantitative Psychology, Statistics, or a related study program;
• Strong analytic and statistical skills;
• Strong computational skills (R, Python or comparable);
• Fluency in written and spoken English;
• Interpersonal and communication skills to effectively collaborate and communicate in academia;
• Experience with inter-disciplinary research; EMA and time-series data; network models and complexity science; science practices (data and code sharing); are a plus;
• Fluency in Dutch (spoken) is a plus.

A full-time (38 hours per week) appointment in this position of initially one year, with the prospect of a total of 4 years of employment. The positions consist of 90% research time and 10% teaching duties. Appointment takes place in accordance with the CAO NU. The salary in the first year is € 2,395 rising to € 3,061 gross per month for a full-time appointment in the fourth year (scale P).

Leiden University offers an attractive benefits package with additional holiday (8%) and end-of-year bonuses (8.3 %). Our individual choices model gives you some freedom to assemble your own set of terms and conditions. For more information, see the website.

Diversity
Diversity and inclusion are integral to the future of psychological science. Those from backgrounds traditionally underrepresented in science are especially encouraged to apply. 

Leiden University

The Faculty of Social Sciences consists of Educational Sciences, Political Science, Psychology, Cultural Anthropology & Development Sociology, and the Center for Science and Technology Studies. The faculty has approximately 5,000 students and 600 employees. Education is provided and research is carried out into various subjects ranging from adoption to political behavior. For more information, see the website of the Faculty of Science.