Optimising Cancer follow-up using mathematical models and AI at EUR

About the role

Erasmus University, TU Delft and Erasmus Medical Centre have partnered through interdisciplinary research and education. As part of this alliance, we are seeking a PhD candidate to develop and evaluate a mathematical model and algorithm that tailors (risk‑based) follow‑up after cancer treatment. The role is highly impactful for ensuring sustainable cancer care in the future and requires an exceptional candidate with strong quantitative and modelling expertise (e.g., POMDP) combined with the interest to work alongside patients and clinicians to improve cancer care.

Responsibilities

• Conduct data analysis using clinical registries.
• Perform evidence synthesis.
• Engage in participatory research with patients and clinicians.
• Apply mathematical modelling, including Partially Observable Markov Decision Processes (POMDP), to develop risk‑based follow‑up strategies.
• Develop AI decision‑making algorithms to determine optimal surveillance intensity, timing, format, and provider.
• Define successful implementation by assessing patient preferences and clinical feasibility of nurse‑led, physician‑led, and online follow‑up models.
• Identify suitable data sources (e.g., cancer registry) and build an extrapolation framework to transfer findings from large datasets to low‑volume tumour streams.

Requirements

• Strong quantitative background with expertise in mathematical modelling, particularly Partially Observable Markov Decision Processes (POMDP).
• Experience or interest in working with clinical data, patient‑centred research, and interdisciplinary teams.
• Skills in data analysis, evidence synthesis, and participatory research methods.
• Ability to develop and evaluate AI‑driven decision‑making algorithms.
• Good communication skills to interact with patients, clinicians, and stakeholders.
• Motivation to contribute to sustainable cancer care and health‑service efficiency.

Application deadline: 30 september 2026