Machine-learning models in the context of physiological state transitions

Machine-learning models in the context of physiological state transitions

Published Deadline Location
4 Feb 1 Mar Leuven

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Job description

This project is the product of a collaboration between IMEC, world leader in nanotechnology and wearables, and the Mind-Body Research group (MBR) and the Centre for Contextual Psychiatry (CCP), two research centers within the Research Group Psychiatry, KU Leuven, Belgium. The MBR group has many years of expertise in stress research and the CCP is internationally recognized for its expertise in measuring psychological variables in daily contexts. Both groups are also closely linked to the University Psychiatric Center (UPC KU Leuven), which facilitates patient access for clinical trials. There is also possibly to collaborate with researchers from the Computational Wellbeing Group at Rice University, Houston, with the option to go abroad on a research visit at that group during the PhD.
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Project
Advances in wearable technology allow for the continuous assessment of physiological data to get a detailed picture of daily-life dynamics associated with the development of mental illness. Specific physiological state transitions may hold prognostic value in the course of development, treatment, and relapse of mental disorders. Computational modelling of the physiological data is a promising approach in predicting this course. Physiological state transitions can be observed in different time-windows. On a momentary level, minute-to-minute changes in physiology, such as in the case of acute stress and recovery from acute stress, may predict specific illness-related behavior and symptoms. On the longer term, more structural alterations in physiology such as chronic stress or patterns in circadian rhythm may signal important phases in illness progression, treatment effects, or relapse.
The successful applicant will develop new computational models to detect daily life markers of state transitions related to mental health. They will work on existing datasets that have been collected within IMEC and the Psychiatry Research Group of the KU Leuven in healthy volunteers and individuals with psychiatric complaints. 

Specifications

KU Leuven

Requirements

  1. Master's degree in electrical or computer engineering, applied mathematics, or related disciplines.
  2. Experience in one or more of the following areas is desirable:
    - Interest in psychopathology
    - Curiosity and ambition to learn new skills and techniques
    - Strong communication and social skills.
  3. Proficient in English, preferably also in Dutch

Conditions of employment

Fixed-term contract: 4 years.

The successful candidate will receive a full-time, 4-year PhD position at KU Leuven and will be embedded in an innovative, high-tech working environment in the MBR and CCP research groups, in close collaboration with IMEC. The PhD candidate will collaborate closely with data scientists at IMEC and there is also a possibility to collaborate with researchers from the Computational Wellbeing Group at Rice University, Houston.

Employer

KU Leuven

A job at KU Leuven? Contributing to top-level teaching and research together with 13,000 colleagues. Sounds like something you’d like to be a part of?
KU Leuven is a large organisation with many different environments. Based at various locations in and around Leuven, and across the rest of Flanders and Brussels, KU Leuven comprises about 100 services, faculties and departments, which are often highly diverse. Respect for local identity and diversity within this large organisation is our strength and a defining characteristic of our culture.
Working at KU Leuven means directly or indirectly contributing to high-quality teaching and innovative research.  Doing a job that has social relevance.
In view of KU Leuven’s international ambitions and the competitiveness inherent in an academic environment, we encourage every employee to develop the same drive and ambition as can be found in the research and teaching to which they contribute.

Specifications

  • Research, development, innovation; IT; PhD
  • Behaviour and society; Natural sciences; Engineering
  • max. 40 hours per week
  • University graduate
  • AT BAP-2021-45

Location

Parijsstraat 72b, 3000, Leuven

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