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University Assistant (prae doc) at the Department of Meteorology and Geophysics
The University of Vienna (20 faculties and centres, 178 fields of study, approx. 9.800 members of staff, about 90.000 students) seeks to fill the position from 01.03.2020 of a
University Assistant (prae doc)
at the Department of Meteorology and Geophysics
Reference number: 10245
We offer a PhD (“prae-doctoral”) position in the field of turbulent tracer dispersion in the atmospheric boundary layer. The position will be embedded in the new research group of Prof. Andreas Stohl on atmospheric transport modelling.
The starting date can be as early as 1 March 2020 and the duration is for four years.
The Department of Meteorology and Geophysics has recently filled two professorship positions (Andreas Stohl and Martin Weissmann, both starting in the beginning of 2020) and is currently in the process of filling a third professorship. This will create an exciting international working environment for many new scientists, large potential for collaboration, and the opportunity for strong personal development.
We seek a PhD student to work in the new research group of A. Stohl. The group will further develop the Lagrangian particle dispersion model FLEXPART (see www.flexpart.eu) and use it as its main working tool for a large range of applications, such as atmospheric energy and moisture transport, pollution transport, or inverse modelling of greenhouse gases.
Dispersion of a pollutant from its source depends strongly on atmospheric turbulence in the atmospheric boundary layer. In Lagrangian particle dispersion models, turbulent tracer dispersion is treated stochastically. The underlying parameterizations in most models (including FLEXPART) are based on decade-old field measurements. The PhD student shall improve these parameterizations based on measurements performed during more recent field experiments such as Project Sagebrush or COMTESSA. This will require a detailed analysis of experimental data, the development of new parameterizations, and the validation of the improved dispersion model utilizing data obtained during atmospheric tracer experiments.
Besides research, the successful candidate is also expected to participate in teaching and the supervision of students. Financial support is available for attending international meetings and visiting international research partners.
Participation in research, teaching and administration:
• Development of improved parameterizations for turbulent tracer dispersion;
• Scientific publications and presentations;
• Participation in teaching and independent teaching of courses as defined by the collective agreement;
• We expect the successful candidate to sign a doctoral thesis agreement within 12-18 months.
• MSc or Diploma degree in meteorology, physics, mathematics, or related subject;
• Good communication skills and ability to work in a team;
• Experience in programming;
• Excellent command of written and spoken English.
Furthermore, the following skills/expertise will be an asset:
• Experience with use of atmospheric (transport) models;
• Good knowledge of statistics;
Your application should be a single PDF file that includes:
• A letter of motivation;
• An academic curriculum vitae;
• A list of publications and presentations, as well as evidence of teaching experience (if available);
• Contact information of two references;
• Degree certificates.
Main research field
Special research fields
Applications including a letter of motivation (German or English) should be submitted via the Job Center to the University of Vienna (
http://jobcenter.univie.ac.at) no later than 15.01.2020, mentioning reference number 10245.
For further information please contact firstname.lastname@example.org.
The University pursues a non-discriminatory employment policy and values equal opportunities, as well as diversity (
http://diversity.univie.ac.at/). The University lays special emphasis on increasing the number of women in senior and in academic positions. Given equal qualifications, preference will be given to female applicants.
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