Eiko Fried
Just added
1 days ago
PhD Position on "Mental disorders as harmful stable states" Leiden University in Netherlands
Degree Level
PhD
Field of study
Psychology
Funding
Full funding availableDeadline
Aug 6, 2026
Country
Netherlands
University
Leiden University

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.
Apply for this position
Keywords
About this position
This PhD position at Leiden University focuses on the project "Mental disorders as harmful stable states," embedded within the NWO Zwaartekracht consortium "New Science of Mental Disorders." The research investigates the network theory claim that mental health problems can become self-maintaining, harmful attractor states, where symptoms, behaviors, and contextual factors reinforce each other over time. The project aims to empirically test this concept using intensive longitudinal patient data, identifying recurring within-person mental health states, their persistence and transitions, and examining their predictive value for clinical outcomes such as relapse, comorbidity, symptom severity, and functioning.
The candidate will also leverage single-case experimental design (SCED) data to explore whether network-informed interventions can be improved by utilizing information about attractor states. The project is highly interdisciplinary, combining clinical psychology, quantitative psychology, statistics, complexity science, and network theory, and offers opportunities for creative input from the candidate.
Supervision is provided by Prof. Dr. Eiko Fried (Leiden University), Prof. Dr. Janna Cousijn (Erasmus University Rotterdam), Dr. Jonas Haslbeck (University of Amsterdam), and Dr. Bart Verkuil (Leiden University). The research environment is collaborative, with regular meetings, joint projects, and participation in the NSMD consortium and graduate schools. The Institute of Psychology at Leiden University is renowned for its diverse research topics, inclusive atmosphere, and commitment to open science and interdisciplinarity.
Applicants must have a Master’s degree in Clinical Psychology, Quantitative Psychology, Statistics, Data Science, or a related field, with strong analytic and statistical skills, ideally with time-series data, and proficiency in statistical programming. Fluency in English and strong interpersonal skills are required. Experience with ecological momentary assessment, interdisciplinary research, network models, complexity science, and open science practices is desirable. Candidates must be willing to reside in the Netherlands and undergo pre-employment screening.
The position offers a full-time contract for one year, extendable for three more years upon positive evaluation. The salary ranges from €3059 to €3881 gross per month, with additional benefits including holiday allowance, end-of-year bonus, pension scheme, full reimbursement of public transport commuting costs, flexible working hours, minimum 29 leave days, hybrid working options, home-working allowance, and university-provided laptop and mobile phone. The university values diversity and inclusion, encouraging applications from underrepresented backgrounds.
To apply, submit your CV (with two academic references) and a 1-page motivation letter via the application link by August 6, 2026. For content questions, contact Prof. Dr. Eiko Fried; for procedural questions, contact Mariska Moreu. More information about employment conditions and the application procedure is available on the university website.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
Official Email
Ask ApplyKite AI
Professors

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.