PhD Candidate Predicting Adherence to Digital Health-Promoting Interventions

**Job Description**
Join an interdisciplinary team to research and predict how individuals engage with digital health interventions using Artificial Intelligence (AI) and machine learning (ML). This Ph.D. position focuses on turning real-world sensor and app data into smarter, personalized digital solutions to support behavior change. The goal is to enhance the effectiveness of digital health interventions by developing AI-based predictive models to anticipate user engagement and behavior, primarily using data from unobtrusive measurements like websites, smartphones, and smartwatches. The research will involve various use cases based on already collected datasets, such as lifestyle interventions and prevention of sexually transmitted diseases.

**Skills & Abilities**
• Strong interest in digital interventions, health promotion, and behavior
• Affinity with data science (complex statistics, machine learning, computational modelling) or willingness to develop relevant skills
• Affinity with health promotion or willingness to develop in that field
• Knowledge in programming (e.g., Python, R, SQL) and data science frameworks (TensorFlow, PyTorch, Scikit-learn) is a plus
• Excellent English language skills

**Qualifications**
Required Degree(s) in:
• Health science
• Health psychology
• Data science
• Statistics

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