Modeling immune–tumor dynamics under metabolic constraints
(ref. BAP
Laatst aangepast: 28/01/26
This project is in the context of a joint PhD and collaboration between the Elia Lab and the Gelens Lab.
The Elia lab focuses on tumor metabolism and immune cell function using state-of-the-art experimental platforms, including mass spectrometry–based metabolomics, physiological media design, live-cell imaging, and flow cytometry.
The Gelens lab specializes in dynamical systems theory, mechanistic and data-driven modeling, and nonlinear analysis of biological systems. Together, the two groups offer a uniquely integrated experimental–theoretical training environment.
Project
Tumors and cytotoxic T cells are engaged in a metabolic arms race. Tumor cells aggressively reshape their microenvironment by consuming key nutrients such as glucose, amino acids, and lipids, while simultaneously accumulating immunosuppressive waste products including lactate, adenosine, and reactive oxygen species. These metabolic constraints critically impair T-cell effector function, promote dysfunctional differentiation, and drive progressive exhaustion.
In this project, the PhD researcher will develop a resource-limited predator–prey modeling framework to study immune–tumor interactions under metabolic stress. Tumor cells are treated as prey and T cells as predators, but with explicit incorporation of shared nutrient competition, waste accumulation, and metabolically driven transitions between T-cell functional states (effector, early exhausted, terminally exhausted). The model will also account for environmental modulation, including temperature dependence of metabolic fluxes and cell-state transitions.
The modeling work will proceed along two complementary tracks. First, mechanistic models based on coupled ordinary differential equations will be constructed and analyzed using nonlinear dynamical systems theory to identify regimes of tumor elimination, stable coexistence, or immune escape. Second, data-driven model discovery approaches will be applied to infer regulatory interactions and nonlinearities directly from experimental time-series data. These approaches build on recent methodological developments in the Gelens lab and ensure that the models remain closely linked to experimental observations.
Model development and analysis will be tightly integrated with quantitative co-culture experiments performed in the Elia lab. These experiments involve tumor cells and CD8⁺ T cells cultured in physiologically relevant media with controlled nutrient and waste conditions. Live-cell imaging, flow cytometry, and metabolomics measurements collected over key stages of T-cell functional progression will be used to calibrate and validate the models. The ultimate goal is to generate metabolic "phase diagrams" that reveal tipping points governing immune control versus tumor escape and to identify actionable metabolic intervention strategies.
The position is available immediately and applications will be considered until the position is filled.
Profile
* You hold a Master's degree in physics, (bio-)engineering, (bio-medicine), computational biology, or a related quantitative discipline
* You are strongly motivated to pursue a PhD at the interface of theory and experiment
* You have experience or a strong interest in mathematical modeling, dynamical systems, or computational biology
* Experience with ordinary differential equations, nonlinear dynamics, data analysis (Python, Matlab, R), and/or machine learning is an asset; experience with data-driven modeling and/or bifurcation theory is a plus
* Interest in immunology, cancer biology, or metabolism is highly appreciated
* Prior wet-lab experience is a plus
* You are able to work independently and enjoy close interdisciplinary collaboration
* You have good communication skills and a strong command of English, both written and spoken
* International working experience is appreciated
Offer
We offer a PhD position with flexible starting date in a stimulating, interdisciplinary research environment at KU Leuven. You will receive advanced training in mathematical modeling, data analysis, biological interpretation, and selected wet-lab experimental techniques, while working closely with experimental scientists. The position provides an excellent foundation for developing an independent research profile. As part of the project, the PhD candidate is expected to apply for a competitive personal fellowship (e.g. an FWO PhD fellowship), with strong support from the supervisors in proposal development and grant writing.
Interested?
For more information please contact Prof. dr. Lendert Gelens, mail: or Prof. dr. Ilaria Elia, mail:
You can apply for this job no later than March 06, 2026 via the online application tool
KU Leuven strives for an inclusive, respectful and socially safe environment. We embrace diversity among individuals and groups as an asset. Open dialogue and differences in perspective are essential for an ambitious research and educational environment. In our commitment to equal opportunity, we recognize the consequences of historical inequalities. We do not accept any form of discrimination based on, but not limited to, gender identity and expression, sexual orientation, age, ethnic or national background, skin colour, religious and philosophical diversity, neurodivergence, employment disability, health, or socioeconomic status. For questions about accessibility or support offered, we are happy to assist you at this email address.
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Tewerkstellingspercentage: Voltijds
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Locatie: Leuven
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Solliciteren tot en met:
06/03/2026 23:59 CET
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Tags: Cellulaire en Moleculaire Geneeskunde, Oncologie, Bio-ingenieurswetenschappen, Geneeskunde, Biologie, Computerwetenschappen, Natuurkunde en Sterrenkunde, Microbiële en Moleculaire systemen, Biosystemen, Ingenieurswetenschappen, Wetenschappen