Studierende finden an der ETH Zürich ein Umfeld, das eigenständiges Denken fördert, Forschende ein Klima, das zu Spitzenleistungen inspiriert.
You will be part of the Institute of Geodesy and Photogrammetry, which is active in researching new innovative space- and ground-based geodetic observation techniques and analysis methods for the long-term, continuous and the real-time monitoring of the environment as well as the Earth system. The newly established professorship in Space Geodesy of Prof. Benedikt Soja will focus on the application of machine learning techniques to geodetic problems, including automated data processing and large-scale time series analysis.
We are seeking a highly motivated PhD student to investigate the positions of thousands of GNSS stations in terms of geophysical signals by means of machine learning. Earthquakes, volcanic activity, or hydrological events cause variations in GNSS station positions. Machine learning techniques enable large-scale processing of time series in order to detect spatio-temporal patterns linked to geophysical phenomena. The PhD student will apply and refine machine learning algorithms related to pattern matching, classification, and prediction to extract signals from GNSS data that could be of great benefit to geosciences and society.
Applicants must hold a master degree in geodesy, geophysics, informatics, or a related field. The successful candidate will have strong analytical skills, and experience in data processing and programming. A background in machine learning, data science, geodesy and/or geophysics would be ideal for this PhD position. Knowledge of the English language is mandatory, knowledge of German is a plus. Good interpersonal skills and the willingness to work in a team of researchers and students are expected.
We look forward to receiving your online application with the following documents:
Applications need to be submitted until April 5, 2020. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
25-03-2024
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