Postdoctoral researcher in wastewater-based epidemiology
The Computational Evolution Group, led by Prof. Dr. Tanja Stadler, in the Department of Biosystems Science and Engineering (D-BSSE) at ETH Zurich works at the interface of mathematics, computer science and evolutionary biology. We develop phylogenetic and phylodynamic methods to understand evolutionary, ecological, epidemiological and developmental processes on different scales based on genetic data.
Our research group is located in Basel, Switzerland’s oldest university city and a European hot-spot for biomedical research. Our department is in close proximity to several other academic research institutes as well as major pharmaceutical and biotech companies. We are also part of the Swiss Institute of Bioinformatics, a major developer and provider of bioinformatics services and resources.
Applications are invited for the position of postdoctoral researcher with Prof. Dr. Tanja Stadler. The position is fixed-term for 2 years with possibility of extension.
Project background
Wastewater-based epidemiology offers a promising approach to track infectious disease dynamics independent from clinical surveillance. By tracking viruses shed into wastewater through time, we can monitor epidemiological dynamics of different diseases and anticipate future trends.
In our previous work on SARS-CoV-2 (https://doi.org/10.1289/EHP10050 ), we showed that wastewater surveillance can not only confirm epidemiological patterns seen in case report data, but also provide independent and complementary epidemiological information. This project will advance wastewater surveillance methods and extend them to other underreported viral pathogens. In particular, we hypothesize that wastewater surveillance can provide epidemiological estimates without biases due to irregular reporting or changing testing strategies.
This project is part of a large 4-year collaborative project on wastewater-based infectious disease surveillance, involving our group, the group of Prof. Dr. Niko Beerenwinkel (D-BSSE, ETH Zurich; statistical modelling and computational data analysis) as well as Dr. Tim Julian (EAWAG; virus detection in wastewater) and Dr. Christoph Ort (EAWAG; characterizing catchment properties).
Job description
You will work as part of a team with Prof. Dr. Tanja Stadler and the other groups involved in the collaboration. Your specific role will to advance modeling and statistical approaches to translate viral loads and viral sequences obtained from wastewater into meaningful, policy-relevant indicators of epidemic trajectories. The project goals are:
- Characterizing the advantages and limitations of wastewater compared to clinical surveillance to inform public health through the example of SARS-CoV-2.
- Quantifying the epidemiological dynamics of endemic coronaviruses and the factors shaping these dynamics, such that long-term scenarios for SARS-CoV-2 can be proposed.
- Detailed real-time tracing of seasonal influenza, aiming to quickly evaluate the risk of a major upcoming wave.
- Applying the developed methods to study the epidemiological dynamics of other viruses monitored in wastewater, in particular non-respiratory infections such as noroviruses and enteroviruses.
Throughout the project any insights we gain into the epidemiological dynamics of ongoing outbreaks that can help inform intervention strategies will be communicated to the Federal Office of Public Health in Switzerland.
We offer
We offer a dynamic and supportive working environment with flexible working hours. ETH Zurich is a family-friendly employer with excellent working conditions and offers highly competitive salaries . The position also comes with funding to attend international conferences and workshops and you will have the opportunity to participate in personal growth and career development opportunities offered by ETH Zurich and the Swiss Institute of Bioinformatics. Switzerland offers top quality of life – including beautiful natural scenery and fantastic infrastructure. We look forward to showing you why Basel, a very international small city ranked the tenth most livable city in the world by Mercer, is a great place to live and work!
Your profile
We are looking for a highly motivated early career researcher with strong quantitative skills. You will have completed a PhD in computational biology, mathematical modelling, biomathematics, epidemiology or a related discipline prior to starting the position. Experience with mathematical epidemiology is beneficial, but not a requirement for the position. A familiarity with NGS sequencing technology, and in particular amplicon sequencing, is further desirable but not required. You will engage in interdisciplinary research as part of a team, so clear and effective communication skills are a priority. We value an open and inclusive group culture. As a member of the Computational Evolution group, you will be expected to help us maintain a positive team dynamic and a welcoming work environment. Our working language in the group is English and no knowledge of German is required. In line with our commitment to an open and inclusive group culture we welcome applications from individuals of all demographic groups and personal backgrounds.
About ETH Zürich
ETH Zurich is one of the world’s leading universities specialising in
science and technology. We are renowned for our excellent education,
cutting-edge fundamental research and direct transfer of new knowledge
into society. Over 30,000 people from more than 120 countries find our
university to be a place that promotes independent thinking and an
environment that inspires excellence. Located in the heart of Europe,
yet forging connections all over the world, we work together to
develop solutions for the global challenges of today and tomorrow.
Curious? So are we.
We look forward to receiving your online application with the following documents:
- Curriculum Vitae including your educational history and full list of publications.
- Letter of motivation of max. 2 pages covering your past research experiences and future research interests, goals and how they would relate to and fit in within the project and the Computational Evolution group’s research domain and activities.
- Names, e-mail addresses, and phone numbers of at least two references, mentioning for each the professional relationship you have with them.
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered. We will review applications as they come in, until the position is filled.
For further information please visit our lab website at https://bsse.ethz.ch/cevo . Questions regarding the position (no applications) should be directed to Dr. Louis du Plessis ([email protected] ).
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