"PhD Candidate Predicting Adherence to Digital Health-Promoting Interventions"

Welcome to Maastricht University! Do you want to understand and predict how people engage with digital health interventions using AI? Join us to turn real-world sensor and app data into smarter, personalized digital solutions that support behavior change.

Our goal: To make digital health interventions more effective by predicting and improving adherence through Artificial Intelligence (AI) and machine learning (ML).

Your colleagues: An interdisciplinary team of scientists working across Maastricht University and FH Joanneum in Austria.

We are seeking a PhD candidate on predicting adherence to digital health-promoting interventions with AI and ML techniques. You will develop AI-based predictive models to anticipate user engagement, primarily using data collected through unobtrusive measurements (e.g., websites, smartphones, smartwatches). The goal is to construct an AI-driven framework that predicts both intervention use (e.g., content exposure, study protocol completion) and behavior. Better adherence prediction is crucial to support the development, tailoring and delivery of health-promoting interventions, and ultimately their effectiveness and success.

The PhD research involves a variety of use cases focused on predicting adherence to various elements of digital interventions to promote health behavior. These use cases are based on already collected datasets. For example:

• Data from a 2-year smartphone-app and Fitbit-supported lifestyle intervention to reduce dementia risk.
• Data from a web-based intervention focused on the prevention of sexually transmitted disease and condom use.

Additional use cases will be explored during the project, also based on your preferences and interests.

You are primarily based at Maastricht University (MU), Maastricht, the Netherlands. There are opportunities for short research visits to FH Joanneum – University of Applied Sciences (FHJ), Graz, Austria. Supervision is organized by dr. Jeroen Bruinsma (MU), dr. Markus Bödenler (FHJ), dr. Rik Crutzen (MU).

What you bring: We’re interested in who you are and what you bring. Do you recognize yourself in this?

• Strong interest in digital interventions, health promotion and behavior.
• A (almost) completed University Master’s degree in a relevant field concerning health (e.g., health science, health psychology) or data analysis (e.g., data science, statistics).
• Affinity with data science (e.g., complex statistics, machine learning or computational modelling) or willingness to develop relevant skills (in case of a degree focused on health).
• Affinity with health promotion or willingness to develop in that field (in case of a degree focused on data science).
• Knowledge in programming (e.g., Python, R, SQL) and data science frameworks (TensorFlow, PyTorch, Scikit-learn) is a plus.
• Excellent English language skills.

What we offer: As a PhD Candidate at Faculty of Health, Medicine and Life Sciences, you will be employed by the most international university in the Netherlands, located in the beautiful city of Maastricht. In addition, we offer you:

• Good employment conditions. The position is graded in scale P according to UFO profile PhD Candidate, with corresponding salary based on experience ranging from €3059 and €3881 gross per month (based on a full-time employment of 38 hours per week). In addition to the monthly salary, an 8.0% holiday allowance and an 8.3% year-end bonus apply.
• An employment contract for a period of 12 months with a scope of 1.0 FTE. Upon a positive evaluation, an extension of 3 years will follow.
• At Maastricht University, the well-being of our employees is of utmost importance, we offer flexible working hours and the possibility to work partly from home if the nature of your position allows it. You will receive a monthly commuting and internet allowance for this. If you work full-time, you will be entitled to 29 vacation days and 4 additional public holidays per year, namely carnival Monday, carnival Tuesday, Good Friday, and Liberation Day. If you choose to accumulate compensation hours, an additional 12 days will be added. Furthermore, you can personalize your employment conditions through a collective labor agreement (CAO) choice model.
• As Maastricht University, we offer various other excellent secondary employment conditions. These include a good pension scheme with the ABP and the opportunity for UM employees to participate in company fitness and make use of the extensive sports facilities that we also offer to our students.
• Last but certainly not least, we provide the space and facilities for your personal and professional development. We facilitate this by offering a wide range of training programs and supporting various well-established initiatives such as 'acknowledge and appreciate'.

The terms of employment at Maastricht University are largely set out in the collective labor agreement of Dutch Universities. In addition, local provisions specific to UM apply.