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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: 10248
We offer a PhD (“prae-doctoral”) position in the field of energy and moisture transport in the atmosphere. 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.
Transport of energy and moisture in the atmosphere is usually considered in a Eulerian framework. However, Lagrangian transport modelling based on atmospheric re-analysis data can offer a different perspective, e.g., to determine the evaporation source regions of precipitation, to identify the role of heat transport during heat waves, or to examine causal relationships between certain atmospheric transport patterns and storm events. The PhD student shall utilize domain-filling simulations with FLEXPART to perform case studies and statistical analyses of energy and moisture transport in the atmosphere. This can include analyses of particular extreme events, as well as global statistics of energy/moisture transport.
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:
• Transport-model assisted analysis of trace constituent data, both in case studies and statistically;
• 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, 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 10248.
For further information please contact email@example.com.
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.