Many current challenges are related to the evolution of species: the spread of pandemics, extinction of species through climate change, and the rise of antibiotic resistance affecting treatment outcomes. Therefore, predicting evolutionary dynamics is highly relevant. Current approaches, such as fitness landscapes, often focus on a single organism, but the environment and communities that micro-organisms live in are highly relevant. As an example we can take antibiotic resistance evolution, which can emerge through the evolution of enzymes that degrade antibiotics. Those enzymes clear the environment of antibiotics and therefore alter the selection on its own population and that of cohabiting populations.
The group of dr. Meike Wortel
focusses on developing mathematical and computational techniques to include the environment, including other species, in the analysis of evolutionary trajectories and apply this to antibiotic resistance evolution and the evolution of microbial communities. To achieve this, the group combines evolutionary approaches with systems biology, that links the intricate networks that make up cells to their overserved behavior at the cell level.
The group is embedded in the Microbiology Theme
at the Swammerdam Institute for Life Sciences, one of the largest research institutes of the Faculty of Sciences at the University of Amsterdam, and affiliated with interdisciplinary collaborations in Systems Biology
and research on Origin and Evolution of Life and Emergence
. The group uses ongoing collaborations to link theory directly to experimental systems, together with the group of prof. de Visser
in Wageningen for antibiotic resistance and the groups in the Amsterdam Microbiome Initiative for (gut) microbiome communities.
To contribute to our research we are looking for an enthusiastic and intrinsically motivated PhD candidate. If you are interested in studying living systems with mathematical models, then this is the position for you! What are you going to do?
You are expected to create and analyse mathematical models of antibiotic resistance evolution and evolution in microbial communities. You are expected to combine existing methods and design new approaches, when necessary. You will start by using data from the ongoing collaboration on antibiotic resistance evolution in laboratory communities and develop models and methods for that system. Then you can apply these methods and techniques in various settings. Tasks and responsibilities:
- complete and defend a PhD thesis within the official appointment duration of four years;
- plan and perform scientific data analysis and experiments in an independent manner;
- critically analyze and interpret results;
- take a leading role in writing manuscripts;
- present your results (inter)national scientific meetings;
- collaborate with international and local researchers;
- participate in the Faculty of Science PhD training programme;
- assist in teaching undergraduates and Master’s students;
- co-supervise MSc/BSc students.