Data Scientist/post-doc in astronomical imaging and machine learning
The Stochastic Information Processing Group (SIP) (http://sip.unige.ch) of Prof. Slava Voloshynovskiy and the Starbursts in the Universe group of Prof. Daniel Schaerer, University of Geneva, Switzerland, have an open data scientist/post-doc position in astronomical imaging and machine learning.
For more details see the full job advertisement.
The applications received by 19 November, 2021 will receive consideration.
THIS POSITION HAS BEEN FILLED
Postdoctoral research position in radio/sub-mm astronomy and signal/data processing
The University of Geneva, Switzerland, announces a postdoctoral position on radio and sub-mm astronomy and signal/data processing of interferometric data in the framework of the Swiss-wide collaborative AstroSignals project funded by the SNF.
AstroSignals is a new interdisciplinary initiative to take advantages of advanced signal processing, data science and high performance computing techniques for new generation large radio-interferometry facilities as the SKA, and for the exploitation of existing interferometers (sub-mm and radio).
The successful candidate will work on available interferometric observations and simulated data to study star-formation and the ISM of distant galaxies. The post-doc will test and exploit different imaging and 3D-data analysis methods, in close collaboration with signal processing and machine learning experts. The candidate will also be encouraged to develop an independent research programme.
The candidate will primarily work with the groups of Profs. Daniel Schaerer and Slava Voloshynovskiy, other AstroSignals teams, and with international collaborations.
The Geneva Observatory and the associated Laboratory of Astrophysics of the Swiss Federal Institute of Technology in Lausanne (EPFL) in Sauverny carry out observational, interpretative and theoretical research in the fields of extra-solar planets, stellar physics, high energy astrophysics, galaxy evolution, and observational cosmology. The Stochastic Information Processing (SIP) group, headed by Slava Voloshynovskiy, focuses on the intersection of image processing, machine learning and information theory for the development of new imaging and data analysis techniques.
The appointment will be for up to three years starting in sept-oct 2021. Qualified candidates are encouraged to send their application including
a CV and publication list, description of research experience and interests, and contact information of three references in a single pdf file via email to the above address. Applications received by 12 february, 2021 will receive consideration. Informal enquiries with Daniel Schaerer ( ) are welcome.
For information on the research groups visit
Standard Swiss Social Security, Accident Insurance and Pension contributions.
Daniel Schaerer, (16 nov 2020)