02/12/2019

University Assistant (prae doc)


  • ORGANISATION/COMPANY
    Faculty of Earth Sciences, Geography and Astronomy
  • RESEARCH FIELD
    GeosciencesOther
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    15/01/2020 00:00 - Europe/Brussels
  • LOCATION
    Austria › Vienna
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Part-time
  • HOURS PER WEEK
    30
  • OFFER STARTING DATE
    01/03/2020
  • REFERENCE NUMBER
    10247
  • MARIE CURIE GRANT AGREEMENT NUMBER
    No

We offer a PhD (“prae-doctoral”) position in the field of inverse modelling. 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.

Inverse modelling is a statistical method that can be used to infer the fluxes of gases or aerosols at the Earth’s surface based on atmospheric concentration or, for some species, deposition measurements. This requires an atmospheric transport model linking the fluxes and observations. For example, temporally and spatially sparse ice core records can be used to determine historical emissions of, e.g., black carbon or heavy metals on the continental scale. Currently still extremely sparse measurements of microplastics in the environment can be used to determine the origins of these plastics, which are currently almost entirely unknown. Or the very dense measurements of greenhouse gases can be used to determine their fluxes at high time and space resolution. The PhD student will apply inverse modelling in one or two research fields such as those described above, collaborating closely with internationally leading measurement groups.

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:
• Inverse modelling of trace constituents;
• 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. Participation in research, teaching and administration:
• Inverse modelling of trace constituents;
• 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.

Benefits

Eligibility criteria

• 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.

Selection process

• 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.

Additional comments

The University of Vienna was founded in 1365 and is the oldest university in the German-speaking world and one of the largest in Central Europe. At present, about 88,000 students are enrolled in 180 courses at the University of Vienna. The University of Vienna is also the largest teaching and research institution in Austria with 8,900 employees, 6,700 of whom are scientists and academics.

Web site for additional job details

Required Research Experiences

  • RESEARCH FIELD
    GeosciencesOther
  • YEARS OF RESEARCH EXPERIENCE
    None

Offer Requirements

Skills/Qualifications

• 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.

Specific Requirements

• 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.

Map Information

Job Work Location Personal Assistance locations
Work location(s)
1 position(s) available at
Department of Meteorology and Geophysics
Austria
VIENNA
Vienna
1010
Universitätsring 1

EURAXESS offer ID: 468453
Posting organisation offer ID: 10247

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