Project context

The recently communicated Safe-and-Sustainable-by-Design (SSbD) framework of the European Union aims to develop new chemicals in a way that they are inherently environmentally safe. Implementation of this goal requires appropriate methods for high-throughput assessment of key environmental hazards, including chemical persistence in the environment. In this self-funded project, we will build on previous work in our group1 to further develop in silico tools to predict removal of chemicals during biological treatmentin wastewater treatment plants (WWTPs). We will generate own monitoring data using our new Orbitrap Astral mass spectrometer and train novel QSBR models directly based on the mass spectrometric data. This work will contribute to our team’s wider efforts to generate and share FAIR biotransformation data, and use them to develop transparent, performant, and easily accessible models for use in industrial and regulatory

contexts.

Your tasks

• You will optimize methods to measure untreated and treated wastewater samples on the Orbitrap Astral instrument such as to maximize MS2 acquisition
• You will develop novel models to predict removal in WWTPs using the thus acquired data
• You will explore additional machine learning and deep learning strategies for improving prediction of removal in WWTPs, including read-across and feature engineering
• You will present results at international conferences and prepare publications in peer-reviewed scientific journals
• You assist the teaching at the Chemistry Department of the University of Zurich

Your profile

• Master’s degree in analytical chemistry, bioinformatics, cheminformatics or related fields ¹
• Hands-on research experience with mass spectrometry
• Skills in data science and/or machine learning are a plus
• Excellent interpersonal skills and oral/written communication skills (English required, German desirable)
• Motivation to work in an interdisciplinary team and across institutions

What we offer

The project will be led by Kathrin Fenner and will be conducted in close collaboration with Heinz Singer (Environmental Chemistry, Eawag). Kathrin Fenner is professor in Environmental Chemistry at the Chemistry Department of the University of Zurich and group leader at the Department of Environmental Chemistry at Eawag. Both Eawag and the University of Zurich are located within the Zürich metropolitan area.

As a PhD student, you will become part of the PhD program offered by the Graduate School of Chemical and Molecular Sciences Zürich. The University of Zurich is a modern employer and offers an excellent working environment where staff can contribute 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 importance to us.

¹ Cordero et al., https://chemrxiv.org/engage/chemrxiv/article-details/6800a831e561f77ed46c22b9

Employment start date will be mutually agreed upon (preferably as soon as possible).
We ask for strongly motivated candidates to submit their applications containing a motivation letter, a research summary of past accomplishments (1 page), a CV (resumé), and one letter of support (or the names and contact details of 2 referees).

For further information, please contact

Prof. Dr. Kathrin Fenner, kathrin.fenner@chem.uzh.ch

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.