Real-Time Stress Triggers & Interventions via Wearables

Utwentecareers; Enschede; Híbrido; EUR 38 000 - 49 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

CAO-NU salary

8% holiday allowance

End-of-year bonus 8.3%

Pension scheme

Leave entitlement

Sports facilities on campus

Parental leave

Training programme

National PhD community

Resumo da oferta

University of Twente invites applications for a PhD student in the Stress in Action project to turn a wearable-based stress toolkit into an active system.

You will review physiological triggers, implement near real-time processing on wearables, test with intensive field data, and study user responses to cues. The collaboration spans seven Dutch universities and centers on improving just-in-time interventions.

Qualificações

• MSc degree in a relevant field.
• Strong interest in ambulatory physiological research and wearables.
• Programming skills in Python, R or similar.
• Affinity with user research and app-based data collection.
• Experience writing research papers.
• Excellent English communication and teamwork.

Responsabilidades

• Review how physiological signals trigger experience-sampling.
• Develop and test triggers on wearables and experience-sampling platforms.
• Evaluate triggers in a two-week intensive study.
• Study user experience of cuing.
• Use daily-life datasets to compare signals and thresholds.
• Design and pilot a context-sensitive stress intervention.

Conhecimentos

Python

R

Multilevel modelling

Machine learning

User research

App-based data collection

Formação académica

MSc degree in biological, health or human factors psychology, health sciences, biomedical technology, human-computer interaction, technical medicine, computer or data science, or a related discipline

Descrição da oferta de emprego

University of Twente invites applications for a PhD student in the Stress in Action project to turn a wearable-based stress toolkit into an active system.

You will review physiological triggers, implement near real-time processing on wearables, test with intensive field data, and study user responses to cues. The collaboration spans seven Dutch universities and centers on improving just-in-time interventions.