See here for currently open positions and Bsc/MSc projects in my group. In addition, I encourage direct applications for projects that have an independent financing, such as Ambizione or Marie-Curie fellowships. For an overview of possible independent Postdoc funding, see here: UZH Postdoc funding.
If you have a project idea and a financing plan, please contact me, sending me your CV, two addresses of academic references as well as a 1–2 page summary of your project plan.
Open PhD and Postdoc positions:
There is currently no open position
Available BSc or MSc projects (thesis projects are primarily targeting UZH and ETHZ students):
- Application of Machine Learning to environmental DNA data for environmental monitoring. MSc Project: Project Description
- Unravelling genetic structure and gene flow patterns in groundwater amphipods from the genus Niphargus using microsatellite analysis. MSc project: Project description
- Discovering the underground: Occurrence and biodiversity of macroinvertebrates in Swiss groundwater systems. Details MSc project: Project description
- The “who is who” of aquatic biodiversity in Swiss rivers. Improving databases for eDNA biodiversity monitoring. Details MSc project: Project description
- Taking the lab to the field: A novel tool to assess biodiversity in river systems- Using a “pocket sequencer” to assess the timescale of eDNA biomonitorings. Details MSc project: Project description
- Measuring aquatic biodiversity in the river Rhine using environmental DNA (eDNA). Details MSc project: Project description
- Hidden in the dark: Ecology and faunistics of groundwater amphipods in Switzerland using a citizen science approach. Details MSc Project: Project description
- Resilience of meta-ecosystems: how openness and diversity buffer for ecosystem functioning under perturbation. Details MSc project: Project description
- Transport and decay of environmental DNA (eDNA) in rivers: Develop laboratory and field experiments to directly release and capture artificial eDNA molecules and compare their detection and quantification to model predictions. Details MSc project: Project description