Eawag, the Swiss Federal Institute of Aquatic Science and Technology, is an internationally networked aquatic research institute within the ETH Domain (Swiss Federal Institutes of Technology). Eawag conducts research, education and expert consulting to achieve the dual goals of meeting direct human needs for water and maintaining the function and integrity of aquatic ecosystems.
The goal of the PhD project
is to study interacting biotic and abiotic drivers of plankton dynamics leading to harmful cyanobacterial blooms (cyanoHABs) in lakes, using observational data and experiments. We aim at studying and modelling plankton food-web changes — including the dynamics of toxic cyanobacterial taxa — by applying new methods for in situ monitoring (e.g. underwater imaging, see the Aquascope
website), and by analysing the data using a machine learning approach. The plankton community data will be complemented with DNA-metabarcoding and quantitation of toxic cyanobacterial genes / genotypes.
The selected PhD candidate will participate in a collaborative, cross-disciplinary project involving four groups in ecology, microbiology, environmental chemistry, and dynamical systems theory, to study the temporal and biological processes leading to the emergence of cyanoHABs. The project aims to understand the ecological and evolutionary mechanisms triggering cyanoHABs in lake ecosystems, and develop predictive models. The PhD student in plankton ecology will be responsible for collection of data from Swiss lakes, apply data mining tools and machine learning to model and forecast community dynamics and cyanoHAB events.
The duration of the PhD position will be 4 years.
The PhD degree will be awarded by ETH-Zurich. The candidate will be based in the group of Phytoplankton Ecology at Eawag in Dübendorf, supervised by Dr Francesco Pomati
. The project is funded in collaboration with the groups of Dr Elisabeth Janssen
, Dr David Johnson
, and Rudolf Rohr
. A total of three PhD students, two Research Assistants and one Postdoc will be hired together as a cluster for this project. The PhD candidates will benefit from close collaboration with the whole project team, including the PIs’ groups and external collaborators. The international and cross-disciplinary nature of this synergistic project will be ideal for promoting skill acquisition, independent thinking and future scientific career development of the student.
We are looking for a highly motivated person with interests in quantitative ecology to integrate limnology and community and/or food-web science with field data and experiments. The project is cross disciplinary and would benefit from a creative and open mind. At least 80% of the work will be computational, while the remaining 20% will be dedicated to field and lab work.
The successful candidate is expected to hold an MSc degree, has experience in ecological data analyses and/or modelling (preferably aquatic/microbial ecology), demonstrated skills in scientific communication (including paper writing), and a willingness to learn and expand skills into machine learning, analysis of images and DNA data. Other desired skills include computer programming (e.g. R and/or Python), experience with machine learning or large datasets, familiarity with community ecology or evolutionary biology principles, phytoplankton and lake ecosystems. Fluency in English is required.
a modern employer and offers an excellent working environment where staff can con-tribute their strengths, experience and ways of thinking. We promote gender equality and are committed to staff diversity and inclusion. The compatibility of career and family is of central im-portance to us. For more information about Eawag and our work conditions please consult www.eawag.ch
. Eawag is located within the Zürich metropolitan area, and the city of Zürich is continuously ranked among the top cities in the world for quality of life and is within close proximity to the Swiss Alps.
The review process of candidates will start on 23 August 2021, therefore submission is encouraged by 22 August 2021. Application should include a cover letter with a concise statement about your previous research, your vision for the future and your motivation to work on this project (2 pages maximum), a curriculum vitae including (if applicable) the list of publications, copies of your academic qualifications; and names and contact information of 2-3 academic references (please do not include letters with the application). The preferred start date will be late 2021 / early 2022.
We look forward to receiving your application. Please send it through this webpage, any other way of applying will not be considered. A click on the button below will take you directly to the application form.