Postdoctoral Researcher in Precision Psychiatry

We are now looking for a postdoctoral researcher for a two-year employment. You will be working with statistical modelling in two different studies. In both studies you will collaborate with colleagues at Oxford University (UK), University of North Carolina Chapel Hill (US) and collaborators in Sweden.

Study 1 is a registry study led by John Wallert and focused on risk factors for suicide among psychiatric patients that have experienced compulsive mental careled. Temporal trends in the risk of suicide and also stratified risks by gender and age will be studied. Forty years of nationwide registry data with over 100,000 recorded compulsory care episodes defines the cohort to be studied. The work involves application of your expertise as epidemiologist/biostatistician to estimate absolute and relative risk of suicide. Your role also involves the production of scientific articles. There is also ample possibility to construct instruments that predict risk based on the risk factors that we will discover, and possibilities to apply more advanced modelling appropriate for large-scale observational data.

In Study 2 you will be working with multimodal data (including genetic data) in a nationwide suicide cohort with the purpose of improving present prediction of suicide aiming to derive and validate better risk models for suicide in the total population. Study 2 also provides the opportunity to apply both well-established statistical modelling and newer machine learning methodology.  

Read more and apply here.

Doctoral (PhD) student position in Precision Psychiatry

📣 We are looking for a PhD student interested in Precision Psychiatry to join our team! 📣

The overarching purpose of your PhD project is to improve routine-care predictions of post cognitive behaviour therapy (CBT) outcomes for common mental disorders. Our developed prediction models will be focused on avoiding unnecessary treatment failures, minimizing adverse long-term health and socioeconomic events, and promoting effective use of psychiatric resources. Today, there is a general lack of accurate prognostic risk tools implemented in routine psychiatric care, which directly hampers our possibilities for timely and cost-effective tailored intervention and care. The main objective of your PhD project is thus to construct and validate prediction models for both clinical CBT outcomes and long-term register outcomes using the world’s largest multimodal database in the field (clinical, register-linked, and genetic data) including 5,000 individuals treated with CBT.

You will be supervised by John Wallert and co-supervised by Christian Rück.

Click here to read more and apply.