Optimising Cancer follow-up using mathematical models and AI

Erasmus Universiteit Rotterdam; Rotterdam; Hybrid; EUR 36,000 - 45,000; Full time

Benefits offered by this job

Flexible & home-based work

Dutch language courses

International environment

Job summary

Erasmus University Rotterdam (EUR) invites applications for a PhD candidate to develop and evaluate a mathematical model and algorithm for risk-based follow-up after cancer treatment. You will combine data analysis, participatory research with patients and clinicians, and AI decision-making to tailor surveillance strategies across Europe.

The project spans systematic review, registry data analysis, and a modelling framework that informs capacity planning and clinical outcomes.

Qualifications

• Demonstrable modelling and algorithmic experience, including POMDPs.
• Ability to engage credibly with clinicians and patients.
• Completed (or near-completed) Master’s degree in a quantitative field.
• Strong Python programming skills and experience with registry data.
• Affinity with qualitative and participatory methods.
• Fluent English; Dutch preferred.
• Independence and persistence for four years of doctoral research.

Skills

Modelling (POMDP)

Clinical engagement

Python programming

Data analysis

Qualitative methods

Doctoral independence

Education

Master's degree (quantitative field)

Tools

POMDP modelling

Job description

Organisational unit Erasmus School of Health Policy & Management (ESHPM)

Employment 1 fte - 1 fte

Introduction

Erasmus University, TU Delft and Erasmus Medical Centre have established a partnership through interdisciplinary research and education. As part of the work in the alliance, we are looking for a PhD candidate to develop and evaluate a mathematical model and algorithm to better tailor (risk-based) follow-up after cancer treatment. The role is highly impactful for ensuring sustainable cancer care in the future, and we are looking for an exceptional candidate with strong quantitative, and modelling (e.g., POMDP) expertise combined with the interest to work with patients and clinicians on improving cancer care. In the role you will combine data analysis using clinical registries, evidence synthesis, participatory research with patients and clinicians, applied modelling, and development of AI decision-making algorithms to answer a question that health services across Europe are struggling with: how much surveillance is enough, for whom, and delivered by whom?

Background

Follow-up after primary cancer treatment is, in several tumour streams, more intensive than the evidence currently supports. Where the aim is recurrence detection, frequent and intensive surveillance shows limited benefit for clinical outcomes while imposing psychological burden and out-of-pocket costs on patients and consuming scarce professional capacity.

These pressures are intensifying. Survivor numbers are rising, early-onset cancers extend the survivorship horizon, treatment is shifting from surgery towards systemic therapy, and complex care is concentrating in fewer specialised centres. Deciding where surveillance capacity is best spent has therefore become a question of workforce sustainability as much as one of clinical effectiveness.

Aim and objectives

The project aims to use modelling to propose risk-based follow-up strategies that match surveillance intensity to individual recurrence risk. It pursues three objectives.

• Optimising follow-up.Determining when, for how long and in what form patients should be seen, and identifying the factors — age, tumour stage, molecular profile, treatment received — on which stratification can be based. Given clinical and molecular characteristics of many tumours, a Partially Observable Markov Decision Process (POMDP) is a preferred approach.
• Defining successful implementation.Engaging patients to understand their concerns and preferences, and assessing the clinical feasibility of alternative follow-up arrangements, including nurse-led, physician-led and online delivery, with attention to professional roles, responsibilities and workload.
• Data and model requirements. Identifying suitable data sources such as the cancer registry, specifying the model along clinical, operational and organisational dimensions through participatory design, and building an extrapolation framework that transfers findings from large datasets to low-volume tumour streams.

Approach

The work combines several strands. A systematic review with LLM-assisted extraction of policy documents updates the international consensus on follow-up and risk stratification. Second, secondary data sources (e.g., cancer registry) will be used to map variation in current practice, estimate (yearly) recurrence incidence, and define the risk factors on which cancer follow-up can be stratified. Focus groups with patients establish what implementation would require of them and focus groups with professionals address feasibility and their own role. These feed a model whose outputs cover capacity and resource use alongside clinical outcomes, with risk factors and organisational constraints — hub-and-spoke versus centralised care, nurse-led delivery — entering as explicit variables.

Colorectal, lung and bladder cancer are the primary candidate tumour streams, with prostate and breast under consideration. Ideally, the project approach and results should be generalisable to other tumour streams.

Job requirements

This project asks two things of you in equal measure: the technical ability to build and run models, and the interpersonal ability to work closely with the patients and clinicians whose care those models describe. Candidates who are strong on only one side will find the project difficult and may not be considered eligible. Specifically, you have:

• demonstrable modelling and algorithmic experience.You have built, programmed and run models yourself — for example discrete-event or capacity models, but specifically POMDPs — and can read and adapt someone else’s model code. You are interested in addressing challenges of scalability, robustness and interpretability in AI decision making. The emphasis in this project is on applying established methods rigorously to a clinical and organisational problem, not on developing new mathematical theory;
• the ability to engage credibly with clinicians and patients.This is the skill we weigh heavily. You can sit in an oncology outpatient clinic and earn the confidence of the professionals working there; you can facilitate a focus group with people living after cancer treatment, with the sensitivity that subject demands; and you can translate technical findings into terms that clinicians, patients and hospital managers can act on. Prior experience in a clinical, patient-facing or participatory research setting is a clear advantage;
• a completed (or nearly completed) Master’s degree in econometrics, mathematics, computer or biomedical sciences, artificial intelligence, operations research, data science, or a related field;
• solid programming skills in Python or a comparable environment, and experience analysing patient-level or registry data;
• affinity with qualitative and participatory methods, or a clear willingness to acquire them: focus groups and participatory design are a substantive part of the project, not an afterthought;
• excellent command of English, written and spoken. Command of Dutch is preferred because we expect focus groups with Dutch patients and professionals form part of the project. Should Dutch not be the preferred language, you are expected to jointly work with Dutch health professionals or students who can moderate these focus groups;
• the independence and persistence that four years of doctoral research require, alongside a genuinely collaborative disposition.

Employment conditions and benefits

• We offer you an internationally oriented and varied job in an enthusiastic team, with excellent working conditions in accordance with the Collective Labour Agreement for Dutch Universities (CAO-NU).
• A structured training programme through the Erasmus Graduate School of Social Sciences and the Humanities, plus a personal budget for courses, conferences and career development. International candidates are supported in learning Dutch through the university’s language courses.
• Embedding in the EMPOWER strategic alliance (ErasmusMC) on a sustainable healthcare workforce, giving you an interdisciplinary network across research and practice.
• Flexible and partly home-based working arrangements, and an international working environment on the Woudestein campus in Rotterdam.

Everything else we offer you, you can find below!

• Everything you need for a good work-life balance : the option to work from home in consultation with your manager, 41 days of paid leave with a 40 hour contract, 8% holiday pay and an 8.3% end-of-year bonus, and a significant discount on a subscription for our on-campus sports centre Opens external !
• Moving to the Netherlands for your job with EUR? Then you may be eligible for the 30%-ruling if you meet the requirements of the Belastingdienst (Dutch tax agency), and with our Dual Career Programme we will also help your partner find the right job for them.

Employer

Erasmus University Rotterdam (EUR) is an internationally oriented university with a strong social orientation in its education and research, as expressed in our mission ‘Creating positive societal impact’. EUR is home to 4.100 academics and professionals and almost 33.000 students from more than 140 countries. Everything we do, we do under the credo The Erasmian Way – Making Minds Matter. We’re global citizens, connecting, entrepreneurial, open-minded, and socially involved. These Erasmian Values function as our internal compass and create EUR’s distinctive and recognizable profile. From these values, with a broad perspective and with an eye for diversity, different backgrounds and opinions, our employees work closely together to solve societal challenges from the dynamic and cosmopolitan city of Rotterdam. Thanks to the high quality and positive societal impact of our research and education, EUR can compete with the top European universities. www.eur.nl .

Faculty / Institute / Central service

About Erasmus University Rotterdam, TU Delft and Erasmus MC

Erasmus MC is one of the largest university medical centres in Europe and, through the Erasmus MC Cancer Institute, a national referral centre for complex oncological care. The Department of Oncologic Surgery combines a high-volume surgical practice with an active clinical research programme, and provides the clinical setting, the contact with patients and clinicians, and the outcome data on which this project depends.

Delft University of Technology, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) is a leading European centre for algorithms and artificial intelligence. Its research on sequential decision-making under uncertainty — including partially observable Markov decision processes, planning and reinforcement learning — provides the methodological foundation and supervision for the modelling work in this project.

Erasmus School of Health Policy & Management is a world-leading school in health policy, health economics and healthcare management. ESHPM works on the organisation, financing, quality and governance of healthcare systems, including workforce sustainability in close collaboration with Erasmus MC. Research is problem-driven and multidisciplinary focussed on questions that reach policy and practice. ESHPM is part of Erasmus University Rotterdam, an international research university with a strong societal orientation and a campus community.

Group

Health Services Management & Organisation is responsible for education and research on management and organisation in healthcare. Our aim is to improve the management and organisation of health services to provide the best value for patients/clients and professionals in healthcare. Research of HSMO covers thefull width of the healthcare sector, managerial scientific domains, and methodologies (qualitative-, quantitative-, design-, and action research). To a large extent, our research is carried out on innovation of the primary process of care delivery, both within and across organizations. The teaching of the department is aligned with its research and is mainly organized around the MSc program in Healthcare Management, which is the largest program in this domain in Europe, and the BSc program in Health Sciences (Gezondheidswetenschappen, Beleid & Management Gezondheidszorg). Courses taught for instance address Organisational Behavior, Health technologies, Quality & Safety, Innovation, Integrated Care, Operations Management, and Financial Management. The staff of the department includes 4 Full professors, 3 Associate professors, 11 Assistant professors, and 21 PhD’s.

Department

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Additional information

The (preferred) start date of this position is 1 December 2026 and you will be based at Campus Woudestein in Erasmus School of Health Policy & Management (ESHPM). This position is for 1 fte. The salary ranges from a minimum of € 3.204 to a maximum of € 4.051 gross per month Scale PhD on a fulltime basis (38 hours), in accordance with the CAO-NU. The initial contract runs for 18 months and is extended for the remaining period following a positive evaluation.

Persons of all gender identities or expressions, sexual orientations, religions, ethnicities, ages, neurodiversities, functional impairments, citizenships, or any other aspect are welcome to apply and join the EUR community.