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. The results are directly relevant to the FOEN and will support regulatory decisions regarding PFASs. Your tasks Develop and validate methods to sample and analyze various PFASs in ambient air Conduct sampling
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100%, Zurich, fixed-term We are seeking a skilled Machine Learning Engineer to join our dynamic team. The ideal candidate will be involved in the development, optimization, and maintenance of our
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, rearing various insect species, and helping students and staff prepare their experiments. Profile You must be a current Bachelor or Master student at ETH or UZH, fluent in English, and comfortable working
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methods and confiscation and prosecution strategies, as well as international cooperation. The aim is two-fold: to build capacity and effectively progress cases to the stage of recovery. We also develop and
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genetic elements, genome plasticity, microbial gene and cellular regulation, antimicrobial resistance or evolution. We welcome all experimental microbial models (e.g. bacteria, archaea, unicellular
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biomedical applications. We also develop experimental techniques to observe and characterise high-speed multiphase fluid phenomena optically and acoustically. The group is part of the Institute of Fluid
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of this project are (1) to improve monitoring efforts by developing widely accessible analytical approaches to quantify chloronitramide and (2) to investigate the impact of common water quality parameters
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100%, Zurich, fixed-term The Chair of Risk, Safety & Uncertainty Quantification (RSUQ) at ETH Zurich develops cutting-edge methodologies in the field of uncertainty quantification (UQ
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100%, Zurich, fixed-term The Chair of Risk, Safety & Uncertainty Quantification (RSUQ) at ETH Zurich develops cutting-edge methodologies in the field of uncertainty quantification (UQ
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support throughout the PhD journey flexibility in designing and pursuing own research ideas within the scope of the overall project collaboration with national and international partners to develop a