PhD position: multimodal machine learning (psych)

University of Fribourg / Lausanne University Hospital
Location: 
Fribourg and Lausanne, Switzerland
Job Type: 
Full Time
Closing Date: 
Sunday, February 25, 2018

We invite applications for a 4-year, fully-funded PhD position at the Laboratory for Psychiatric Neuroscience and Psychotherapy of the University of Fribourg, with joint supervision at the Department of Radiology, Lausanne University Hospital (CHUV) and the Advanced Clinical Imaging Technology group, Siemens Healthineers.

The project seeks to develop novel and reliable machine learning tools for clinical diagnosis of neuropsychiatric disorders, in particular psychosis, using ‘deep sampling’ with multimodal brain imaging data (structural, functional, and diffusion MRI, simultaneous near infrared spectroscopy (NIRS) - electroencephalography (EEG)), biomarker data, and genetic data.

This involves healthy controls and psychiatric populations, including psychotic patients. Experimental settings include resting-state and social interaction paradigms. In terms of methods development, the project is placed in a machine learning setting, where the goal is to develop algorithms for individual diagnosis, disease subtyping, and prognosis, rather than group analysis.

The candidate will have access to state of the art data acquisition and computing facilities, including a brand new dedicated clinical EEG-fNIRS room, thousands of compute cores, petabytes of storage, and GPUs. Compensation is very competitive internationally.

Duties:

  • Data acquisition, management, and analysis
  • Algorithm development using Python, R, Matlab
  • Publications writing and conference presentations
  • Research collaboration with international partners

Applicant profile:

  • Master’s degree in computer science, electrical engineering, physics, or related field
  • Good training in linear algebra and statistics
  • English proficiency

Informal inquiries are welcome at jonas.richiardi@chuv.ch (technical co-adviser) or pascal.missonnier@unifr.ch (clinical co-adviser).

Formal applications including cover letter, CV, list of publications, and copy of all degrees should be sent to marie.tamm@unifr.ch until the 25th of February, 2018