Optimising Cancer follow-up using mathematical models and AI

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.

Postdoctoral Researcher in Global Health Economics – BEACON-HD

Are you interested in leading applied research within a large-scale field experiment aimed at improving the management of chronic disease in low-resource settings? Do you want to help make healthcare delivery more effective, efficient and equitable for people living with hypertension and diabetes in Sub-Saharan Africa?

We offer a post-Doc opportunity for 36 months (90% research, 10% teaching) within BEACON-HD, a large EU Horizon Europe-funded international consortium project.

BEACON-HD is testing two promising implementation strategies, telemedicine with self-monitoring and community-based medication delivery, through a large-scale field experiment in rural Rwanda and Uganda. The project combines this field experiment with qualitative, behavioral and economic research to understand not only whether these strategies work, but how, for whom, and at what cost.

As a postdoctoral researcher, you will take a leading role in the economic and equity work package, working closely with the project's PI and the wider consortium. Your responsibilities will include:

• Contributing to and helping coordinate the BEACON-HD field experiment, from the design of data collection instruments to implementation, analysis and interpretation of results, in close collaboration with consortium partners across Europe, Rwanda and Uganda.
• Leading the collection, quality assurance and analysis of data on costs, resource use and outcomes together with our in-country partners, including field visits to Rwanda and/or Uganda.
• Building and extending a decision-analytic (Markov) model to estimate the cost-effectiveness of telemedicine with self-monitoring and community medication delivery, relative to standard care, from the perspective of the public health systems in both countries.
• Leading a budget-impact analysis assessing the short- and medium-term financial implications of scaling up these strategies.
• Leading an equity-modelling study evaluating how the implementation strategies affect health outcomes across socioeconomic subgroups, and their potential to contribute to universal health coverage.
• Co-authoring peer-reviewed publications and presenting findings at international conferences.
• Contributing to the day-to-day coordination of the work package

  This postdoc position combines field-based data collection and analysis with decision-analytic modelling and applied econometric work. It offers the opportunity to generate new methodological and empirical insights into the evaluation of health-system-strengthening strategies, helping to guide fairer and more efficient healthcare policy in low- and middle-income countries.

Data Support Lead & Faculty Liaison

As Faculty Liaison

• You serve as the primary point of contact for academic and support staff within ESHPM and ESSB - Pedagogical Sciences.
• You maintain and strengthen relationships between the University Library and both faculties, proactively identifying developments in research and education.
• You are responsible for acquisition of scholarly content, maintain contacts with publishers and manage specific content budgets.
• You contribute to University Library-wide projects and collaborate closely with fellow Faculty Liaisons.

As Data Support Lead

• You coordinate and lead the Data Support team, which consists of ten professionals with diverse areas of expertise, facilitating effective collaboration.
• You support your team members in their personal and professional development, including through development conversations.
• You promote effective collaboration with the research data community (within the team, the University Library, Erasmus University Rotterdam, and at a national level).
• You keep up to date with developments in the field of research data and research data infrastructures, and translate these into high-quality services.
• You guide the implementation of the team's annual, ensuring alignment with the strategic priorities of the University Library, and contribute to the development of future strategies and plans for the team.
• You contribute to strategic workforce planning.

Data Support Lead & Faculty Liaison

Als faculty liaison

• Ben je het primaire aanspreekpunt voor academisch en ondersteunend personeel binnen ESHPM en ESSB (specifiek voor Pedagogische wetenschappen).
• Onderhoud en versterk je de relaties tussen de UB en beide faculteiten, en signaleer je actief relevante ontwikkelingen in onderzoek en onderwijs.
• Acquireer je onderzoeks- en onderwijsliteratuur, onderhoud je contacten met uitgevers en beheer je het collectiebudget.
• Draag je bij aan UB-brede projecten en werk je nauw samen met collega faculty liaisons.

Als teamleider Data Support:

• Coördineer en leid je het team Data Support, bestaande uit tien professionals met uiteenlopende expertises.
• Ondersteun je teamleden in hun persoonlijke en professionele ontwikkelingen o.a. via ontwikkelgesprekken.
• Bevorder je een effectieve samenwerking met de onderzoeksdata-community (binnen het team, binnen de UB, binnen de EUR en nationaal).
• Volg je de ontwikkelingen op het gebied van onderzoeksdata en – infrastructuren en weet deze te vertalen naar een kwalitatieve dienstverlening.
• Begeleid je de uitvoering van het jaarplan van het team, waarbij je aansluiting zoekt en vindt op de strategische prioriteiten van de UB en draag jij bij aan de ontwikkeling van toekomstige strategieën en plannen voor het team.
• Denk je mee over de strategische personeelsplanning.

Lecturer Strategic Management & Entrepreneurship

Becoming one of our lecturers, you join a dynamic and international department of dedicated educators and academics who engage in high-quality research and teaching.

RSM’s MSc Strategic Entrepreneurship programme addresses core topics in the field of entrepreneurship, the startup lifecycle, and the startup ecosystem. Students work on opportunity recognition and validation, business model design, entrepreneurial finance and fundraising, venture growth and scaling, and corporate venturing and innovation. They learn how to combine academic theory with applied, evidence-based practice.

This programme culminates in a team-based master thesis trajectory. Here, you are part of a dedicated team of lecturers who guide and supervise the students as they conduct original empirical research on an entrepreneurial question, supported by clinic and plenary sessions.