PhD Position in Modelling Epidemic Dynamics and Viral Evolution

About us:

The ICBM is an interdisciplinary research institute dedicated to fundamental and applied marine science. More than 20 research groups – spanning chemistry, biology, physics, and mathematical modelling – collaborate to understand the functioning environmental systems.

The advertised PhD position is offered within the Mathematical Modelling group of Prof. Dr. Bernd Blasius and is part of the DREAM-EP project (Data-informed Responsive Epidemic Analysis and Multiscale-Modelling for Epidemic Preparedness). This project aims to transform how we understand, model, and forecast infectious disease dynamics. Drawing on extensive high-resolution datasets from the COVID-19 pandemic, including SARS-CoV-2 evolution, contact networks, daily mobility in Germany, and global air-traffic patterns, we will develop a data-driven ecosystem for robust epidemic forecasting.

DREAM-EP integrates approaches from epidemiology, adaptive networks, machine learning, AI, statistical modelling, and evolutionary theory to create a stable and scalable forecasting framework for emerging infectious diseases, with a focus on Germany.

Your tasks:

1. Spatial Structure and Responsiveness (in collaboration with Dirk Brockmann and Thilo Gross)

You will investigate how mobility networks changed during the COVID-19 pandemic across multiple spatial scales, from global air traffic to district-level mobility in Germany.

Key responsibilities:

• Characterize mobility networks using standard and multiscale network metrics and quantify changes during the pandemic
• Assess how changes in network structure affect disease spread and feedback dynamics
• Apply statistical mobility models (e.g., gravity and radiation models) to fill data gaps and estimate cross-border mobility
• Contributing to a general framework for evaluating the responsiveness and vulnerability of spatial networks during epidemics

2. Variant Dynamics and Viral Evolution (in collaboration with Christian Drosten)

You will study fundamental principles that govern the evolution of viral phenotypes within multiscale, network-structured populations and their impact on epidemic dynamics.

Key responsibilities:

• Analyze the interplay between viral evolution and epidemic dynamics using COVID-19 in Germany as a case example
• Develop epidemiological models that integrate viral phenotype changes and population immunity
• Construct statistical models of viral evolutionary landscapes informed by biological and network constraints
• Integrating evolutionary and epidemiological models to assess predictability versus stochasticity in variant emergence
• Contribute to risk assessments for the emergence of novel viral strains

Your profile:

Qualifying academic university degree (Master or Diploma (not of a University of Applied Sciences)) in physics, applied mathematics, computational biology, data science or a related discipline. Experience in mathematical modelling, theoretical ecology, or epidemiology is essential. Familiarity with complex network theory, evolutionary processes, or modelling of infectious diseases is highly desirable. Applicants should be fluent in written and spoken English, have strong programming skills (e.g., Python, Julia, Matlab) and show a strong interest in multidisciplinary teamwork.

Our standards:

The University of Oldenburg is dedicated to increase the percentage of female employees in the field of science. Therefore, female candidates are strongly encouraged to apply. In accordance to § 21 Section 3 NHG, female candidates with equal qualifications will be preferentially considered. Applicants with disabilities will be given preference in case of equal qualification.