PhD Position in AI-Driven Exposomic Risk Prediction and Longitudinal Health Monitoring

1 - Working at the VUB

For more than 50 years, the Vrije Universiteit Brussel has stood for freedom, equality and solidarity, and this is very much alive on our campuses among students and staff alike. 

At the VUB, you will find a diverse collection of personalities: innovators pur sang, but above all people who are 100% their authentic selves. With some 4,000 employees, we are the largest Dutch-speaking employer, in the private sector, in Brussels; an international city with which we are only too happy to connect and where (around) our 4 campuses are located. 

Add to this our principle of free research - in which self-reflection, a critical attitude and an open, creative mind around scientific and social issues are central - and you have a university that is fundamentally groundbreaking and pioneering in education and research. In short: the VUB all over again. 

Moreover, the VUB is a member of EUTOPIA, an alliance of like-minded European universities, all ready to reinvent themselves.

2 - Position description

The Faculty of Engineering, Department Electronics and Informatics, Research Group Research-Development-Innovation is looking for a PhD-student with a doctoral grant. 

We invite applicants for a fully funded PhD position in machine learning, AI, and data science for public health within the Electronics & Informatics Department (ETRO) of Vrije Universiteit Brussel (VUB). The PhD is embedded in the Brussels Environmental Exposome (BEE) project, a large interdisciplinary research project funded by Innoviris, involving VUB, UzB, ULB and Sciensano.

The goal of BEE is to develop a next-generation exposomic risk modelling framework that integrates environmental exposures, socioeconomic context, and health data to understand, predict and prevent cardiovascular, neurovascular and other non-communicable diseases (NCDs) in the Brussels Capital Region.

Research Context

Urban populations are exposed to a complex mixture of environmental stressors, including air pollution, heat, noise, green space, and light pollution, that interact with socioeconomic vulnerability and health history to shape disease risk. Yet most clinical risk models ignore this exposome.

In BEE, we will build explainable, physics-guided, GeoAI-driven models that:

• Predict acute and chronic NCD risks at the population scale
• Identify vulnerable neighbourhoods and subgroups
• Support public health policy, prevention and hospital planning
• Provide meaningful feedback to patients, clinicians and policymakers

The PhD will work at the interface of machine learning, deep learning, geospatial AI, causal modelling, and digital health systems.

Your Role

You will develop the core AI and data-driven models that transform large-scale exposomic and health data into actionable risk predictions and feedback systems.

You will:

• Design spatio-temporal machine learning models that integrate:
• Air pollution, weather, noise, green space, urban form;
• Socioeconomic and demographic data;
• Hospital admissions and mortality records;
• Develop physics-guided and graph-based models for high-resolution environmental exposure estimation;
• Build explainable AI pipelines to identify which exposures matter most, and which populations and locations are most vulnerable;
• Combine deep learning with causal inference to distinguish correlation from causal environmental effects;

• Extend the population-level models to longitudinal patient trajectories;
• Design dynamic risk models that evolve over time with changing exposures;
• Develop feedback mechanisms that translate AI predictions into citizen-facing environmental health insights and clinician- and policymaker-relevant risk dashboards.

What You Will Work With

You will have access to one of the richest exposomic datasets in Belgium, including:

• Nationwide hospital admission data (ICD-coded CVD, NVD, NCDs);
• High-resolution environmental maps (PM2.5, NO2, UFP, noise, temperature, greenspace);
• Socioeconomic and neighbourhood indicators;
• Influenza-like illness and mortality records;

All data are geocoded, anonymised and linked through a secure RedCap-based ecosystem.

For this function, our Brussels Humanities, Sciences & Engineering Campus (Elsene) will serve as your home base. 

3 - Profile

What do we expect from you?

• We are looking for a highly motivated PhD candidate with:

  • a Master’s degree in Computer Science, AI, Data Science, Engineering, Biomedical Engineering, or a related field;
  • a strong interest in machine learning for health, environment or public policy;
  • an experience with Deep learning, Time-series or spatio-temporal modelling, Graph neural networks or geospatial data and Explainable AI or causal inference;
  • strong programming skills (Python required);
  • the ability to work in an interdisciplinary medical–AI–public-health team;
  • Good command of English;

  Experience with environmental data, epidemiology or health informatics is a plus, but not required.

• What We Offer:

  • A 4-year fully funded PhD position;
  • A unique position at the intersection of: AI, Environmental science, Medicine and Public health policy;
  • Daily supervision within VUB-ETRO and close collaboration with UZ Brussel clinicians and IT department, ULB environmental epidemiologists, and Sciensano public-health scientists;
  • Access to real-world hospital and exposome data;
  • A strong publication and international conference trajectory;
  • A stimulating, international research environment at ETRO-VUB;

  Your main workplace will be the VUB Etterbeek campus (Pleinlaan 2, Brussels), with regular interaction with hospital and public health partners.

• You have not performed any works in the execution of a mandate as an assistant, paid from operating resources, over a total (cumulated) period of more than 12 months.

• As a (non-)EEA national, meet the conditions for obtaining a valid permit for VUB and comply with the VUB residence requirements. More info here.

The VUB wants to be a reflection of the society where everyone's talent is valued, regardless of gender, age, religion, skin color, migration background, disability and neurodiversity.

4 - Offer

Are you going to be our new colleague?

You’ll be offered a full-time PhD-scholarship, for 12 months (extendable up to max. 48 months, on condition of the positive evaluation of the PhD activities), with planned starting date 01/03/2026. 

You’ll receive a grant linked to one of the scales set by the government.

IMPORTANT: The effective result of the doctorate scholarship is subject to the condition precedent of your enrolment as a doctorate student at the university.

At the VUB, you’re guaranteed an open, involved and diverse workplace where you are offered opportunities to (further) build on your career.

As well as this, you will also enjoy various other benefits:

• Extensive homeworking options, a telework allowance of 50 euros per month OR an internet fee of 20 euros per month;
• An open and informal working environment where attention is paid to work-life balance, and exceptional holiday arrangements with 35 days of leave (based on a fulltime contract), closure between Christmas and New Year and 3 extra leave days;
• Cost-free hospitalisation insurance;
• Full reimbursement of your home-to-work commute with public transport according to VUB-policy, and/or compensation if you come by bike; 
• A wide selection of meals in our campus restaurants at attractive prices;
• Excellent and affordable facilities for sport and exercise, a range of discounts via Benefits@Work (in  all kinds of shops, on flights, in petrol stations, amusement parks...) and Ecocheques; 
• Nursery near campus, discount on holiday camps; 
• The space to form your job content and to continuously learn through our VUB learning platforms and training courses;
• And finally: great colleagues with a healthy drive.

5 - Interested?

Is this the job you’ve been dreaming of?

Then apply, at the latest on 01/02/2026, via jobs.vub.be, and upload the following documents:

• your CV;
• your motivation letter;
• your diploma (not applicable for VUB alumni);
• your cademic transcripts and (optional) links to GitHub, publications or previous projects.

Our application process is as follows (subject to change):

• step 1: an initial selection based on your application file; 
• step 2: a job interview.

Do you have questions about the job content? Contact Prof. Nikolaos Deligiannis at Nikolaos.Deligiannis@vub.be or on +32 (0)2 629 1683.

Would you like to know what it’s like to work at the VUB? Go to jobs.vub.be, and find all there is to know about our campuses, benefits, strategic goals and your future colleagues.

Would you like more information about EUTOPIA? Go to eutopia-university.eu, and read more about the role of the VUB in the development of the EUTOPIA alliance.