In collaboration with project partners at Peking University, China: Perform measurement campaigns in Beijing, China and at the PSI smog chambers with a wide range of aerosol instrumentation (laser-based instruments, aerosol toxicity analyzer, mass spectrometers); Statistical analysis and interpretation of the large and varied data sets resulting from these measurement campaigns; Collaboration within the group and external project partners; Writing high quality peer-reviewed publications; PhD thesis at ETH Zurich, Switzerland
Master degree in physics, chemistry, environmental science or similar; Very good English language skills; Strong programming skills (e.g. Python, R, Matlab, Igor), ideally in a statistical/data science context; Experience in experimental work, ideally with aerosols; Interest in atmospheric processes combined with initiative and enthusiasm to conduct research in a multidisciplinary, international team
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For the Aerosol Physics Group of the Laboratory of Atmospheric Chemistry we are looking for a PhD Student in experimental research on the health effects of aerosol particles Your tasks In collaboration with project partners at Peking University, China: Perform measurement campaigns in Beijing, China and at the PSI smog chambers with a wide range of aerosol instrumentation (laser-based instruments, aerosol toxicity analyzer, mass spectrometers) Statistical analysis and interpretation of the large and varied data sets resulting from these measurement campaigns Collaboration within the group and external project partners Writing high quality peer-reviewed publications PhD thesis at ETH Zurich, Switzerland Your profile Master degree in physics, chemistry, environmental science or similar Very good English language skills Strong programming skills (e.g. Python, R, Matlab, Igor), ideally in a statistical/data science context Experience in experimental work, ideally with aerosols Interest in atmospheric processes combined with initiative and enthusiasm to conduct research in a multidisciplinary, international team We offer Our institution is based on an interdisciplinary, innovative and dynamic collaboration. You will profit from a systematic training on the job, in addition to personal development possibilities and our pronounced vocational training culture. If you wish to optimally combine work and family life or other personal interests, we are able to support you with our modern employment conditions and the on-site infrastructure. For further information, please contact Dr Robin Modini, phone 41 56 310 57 31. Please submit your application online by 6 March 2020 (including addresses of referees) for the position as a PhD Student (index no. 5502-00). 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