New article accepted for publication in Translational Psychiatry

A new article just got accepted for publication in the Translational Psychiatry.

Predicting remission after internet-delivered psychotherapy in patients with depression using machine learning and multi-modal data

Authors: John Wallert, Julia Boberg, Viktor Kaldo, David Mataix-Cols, Oskar Flygare, James Crowley, Matthew Halvorsen, Fehmi Ben Abdesslem, Magnus Boman, Evelyn Andersson, Nils Hentati Isacsson, Ekaterina Ivanova and Christian Rück.

Interesting reading ahead!

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.