DiaLink Palestine: R&D of a digital health lab and low-bandwidth mHealth tools

Organisation/Company KU LEUVEN Research Field Engineering Computer engineering Engineering Biomedical engineering Computer science Other Computer science Informatics Researcher Profile First Stage Researcher (R1) Application Deadline 30 Oct 2026 - 23:59 (UTC) Country Belgium Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Feb 2027 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number BAP-2026-565 Marie Curie Grant Agreement Number 0 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

DiaLink Palestine addresses disrupted continuity of Type 2 Diabetes care in conflict-affected Palestinian settings. Anchored at PPU's College of Medicine and Health Sciences, the project will establish a Digital Health Living Lab and co-create an inclusive, low-bandwidth mHealth tool, an explainable clinical decision support system, and blended patient/clinician/community health-worker pathways. The work combines human-computer interaction, digital health, implementation research, clinical data and equity-centred evaluation. The successful candidate will help connect the Digital Health Living Lab, pilot sites and the joint PPU-KU Leuven research programme. The PhD has a clear engineering focus: developing and evaluating human-centred interactive systems for conflict-resilient diabetes care. The exact doctoral proposal will be refined with the supervisors and doctoral school within the approved DiaLink outcomes.

• Study how conflict, connectivity constraints, health literacy, gender, disability, geography and care workflows shape equitable digital diabetes care.
• Design, implement and evaluate human-centred, offline-first interactive systems that integrate optimization algorithms, machine learning, explainable AI and interactive visual interfaces, enabling patients and healthcare professionals to understand, steer and collaborate with AI-supported decision tools.
• Support baseline, implementation and mixed-methods evaluation; manage reproducible, secure research workflows.
• Assess usability, trust, adoption, continuity-of-care and equity outcomes, including subgroup differences and unintended burdens.
• Contribute to ethics, privacy-by-design, data governance, algorithm safety, open/reusable project outputs, publications and uptake materials.
• Contribute to PPU capacity strengthening, teaching, supervision, stakeholder learning and the National Diabetes Digital Toolkit.
• A master's degree, completed by the appointment/admission deadline, in engineering, engineering technology, computer science, computer engineering, artificial intelligence, data science, human-centred, human‑computer interaction, biomedical engineering, information systems or a closely related technical discipline that clearly demonstrates engineering capability.
• Academic results that satisfy KU Leuven's doctoral admission requirements: normally a relevant master's degree obtained with at least distinction, or an internationally equivalent result, unless the candidate has otherwise distinguished themselves through high-quality scientific publications or design-oriented achievements.
• Demonstrated strong Python programming and practical experience with Git/version control, databases, mobile prototyping and relevant AI/XAI libraries (for example, scikit-learn, PyTorch or TensorFlow, and SHAP or LIME, or equivalents), supported by a thesis, code repository, software prototype or comparable technical work.
• Strong research potential and ability to work across clinical, technical and community settings.
• Strong spoken and written English. Arabic proficiency is required for direct field engagement or must be covered through an approved fieldwork arrangement.
• Ability and willingness to undertake the planned Belgium research periods, while recognising that travel remains subject to visa and security feasibility.

We particularly value

• Experience in applied AI/HCI or distributed systems and architectures, including one or more of the following: optimisation, machine learning/XAI, interactive visualisation, offline-first or mobile systems, secure data synchronisation and software engineering.
• Experience with user-centred or participatory design, usability/accessibility, mixed-methods research, digital health, or work with patients, clinicians, community organisations or health services.
• Evidence of careful research practice: ethics, privacy, secure data handling, reproducibility and clear communication.
• Commitment to Leave No One Behind, gender/equity analysis, accessibility and culturally safe engagement.

Selection process

Selection will be conducted by a joint committee including the PPU promoter or relevant academic representative and the KU Leuven promoters. Conflicts of interest will