PI - PhD in Neurobiological and digital phenotyping towards digital mental health interventions[...]
Responder al anuncioUniversidad de Deusto - Investigación
Descripción de la oferta
Purpose of the position:
Mental health problems are increasing worldwide. Major depressive disorder (MDD) is considered the worldwide leading source of disability. Therapeutic approaches are not fully understood and still improvable. Behavioral activation (BA), a successful therapeutic approach for nearly 50 years, increases activation by means of establishing short, and rewarding experiences in patients’ daily life, e. g. , taking a shower. Current research clearly supports the effects of BA on MDD when comparing it to no intervention. However, BA alone is not superior to other specific forms of psychotherapy.
To improve BA, we need to better understand the behavioral and neurobiological underpinnings. Most recently, researchers identified a new potential starting point for treating MDD: the momentary relationship between physical activity and feelings of energy in everyday life. While past research focused on exercise for treating MDD, we and others found that not sports (e. g. , jogging) but everyday physical activity (e. g. , walking stairs) improves energy.
This position assigned to a project called MASE has as its main research objective the application of artificial intelligence to identify, test, proof, and refine neurobiological phenotype natural environment feature (e. g. , time, place, context) combinations for the administration of individualized nonexercise activity interventions to reliably increase momentary subjective energy as an expedient prevention of and treatment strategy for major depressive disorder.
The hypothesis for this research are 1) different phenotype features of the structural covariance network will increase ASEA prediction in the three follow-up datasets, and 2) specific phenotype-tailored ASEA-feature (e. g. , nonexercise type, time, place, context) combinations will provide resilience and thus predict improved depression ratings in the two questionnaire follow-ups at months 6 and 12.
The objectives of this research conducted under MASE project context will be: a) use artificial intelligence to identify where and when nonexercise activity helps people with certain brain properties, and b) develop and design a smartphone app that delivers ASEA (real-life physical activity-subjective energy association) interventions and provides suggestions when and where to engage in which short nonexercise activity to maximize participation rates.
Title of the project to be incorporated:
MASE, Neurobiological And Digital Phenotyping Towards Digital Mental Health Interventions In Depression
PI and / or project manager:
Amaia Méndez Zorrilla and Begoña García-Zapirain
Endowment of the contract:
25. 973, 10 € / year. 2 years (extendable to 3 years)
Funding Entity:
MASE. COFUND 2 2023. Eranet Neuron, Call 2023. PCI2024-153469.
Requisitos
Qualifications: PhD student.
Experience required:
- Data science and artificial intelligence applied to depression prediction and characterization, and its relation with physical activity.
- Experience in writing scientific publications and reports.
Application:
The University of Deusto carries out this call within the framework of General call for Grants allocated to research projects or groups to pursue Doctoral Studies.
For more information on this call, please click on the link provided.
Steps to apply:
- Register at the Deusto Career opportunities website (click on the blue "register" button).
- Submit an official academic transcript of previous official university studies (1st and 2nd cycle), issued by the corresponding unit.
The academic certificate must state the name of the degree programme, the subjects that make up the course syllabus, the subjects passed, the grades obtained, and the dates on which they were obtained. The transcript should show the average mark from 0 to 10.
If the studies have been completed abroad, an official academic certificate must be submitted as well as a sworn translation thereof, provided that it is not in one of the two co-official languages of the Basque Autonomous Community or in English.
In all cases, the certificate or other supporting document must state the maximum and minimum grades within the corresponding assessment system and the minimum grade required to pass.
In addition, the official certificate from the Spanish Ministry of Education, Culture and Sport (MECD) or ANECA indicating the average grade of the academic transcript within the Spanish evaluation system must be submitted.
- Curriculum vitae.
- Enrollment in the PhD Engineering program at the University of Deusto.
Application and deadline:
- Complete the form on the Deusto Job Offers website.
- Deadline: August 28th, 2024 at 23:59 local time.
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