University assistant (post-doc) in Numerical Weather Prediction and Data Assimilation (3+3 years)

The research group “Numerical Weather Prediction (NWP) and Data Assimilation” led by Prof. Martin Weissmann is part of the Department of Meteorology and Geophysics. One major focus of our research is the assimilation and impact of novel satellite observations as e.g. cloud-affected infrared and visible radiances as well as Aeolus satellite wind lidar observations. 

Further information on our group and research activities is available on our website: https://img.univie.ac.at/en/research/nwp-and-data-assimilation/

What we are looking for:

We are looking for an enthusiastic post-doc to join our group. The new group member shall either propose his/her research plan that complements the current research activities of the group or work on the impact of Aeolus satellite wind lidar observations in global NWP models (see below).
The Aeolus satellite has filled a long-lasting gap in the global observing system by providing wind profiles with nearly global coverage. The assimilation of its observations has led to remarkable improvements in the skill of global NWP models. The candidate shall build upon preceding work of the group (Martin et al. 2021, 2023a and 2023b; Borne et al. 2023 and 2024) and analyse global data denial experiments from ECMWF and DWD to investigate which are the key dynamical processes leading to improvements in NWP skill by assimilating Aeolus observations. Particular focus shall be given to the ability of Aeolus to constrain the divergent wind in the extratropics and vertical shear in the tropics.

The envisioned starting date is July 2024 or as soon as possible thereafter. The position is initially limited to 3 years with the possibility of an extension for another 3 years. 

Tasks of the position:

You actively participate in research, teaching & administration, which means:

• You conduct research on the impact of Aeolus or a proposed topic.
• You disseminate the results in peer-reviewed publications and conference presentations.
• You teach independently in our BSc and MSC curricula within the scope of the provisions of the collective bargaining agreement.
• You support the other group members in technical and scientific concerns. 
• You contribute to project proposals.
• You contribute to organizational and administrative tasks. 

Required and desirable qualification: 

• PhD in meteorology, physics or a related subject (required);
• Good communication skills and ability to work in a team (required);
• Profound programming skills (required);
• Experience in numerical modelling or the analysis of NWP model output (required); 
• Excellent command of written and spoken English (required);
• Expertise in data assimilation (desirable)

What we offer:

Fair salary plus health care and social benefits: The basic salary of EUR 4,752,30 (14 times a year) increases if we can credit professional experience.

An opportunity to push your career further: You have the possibility to acquire a habilitation.

Living in the liveliest city of the world according to multiple international ratings (Economist, Mercer and Monocle).

Work-life balance: Flexible working hours and the possibility of home office at an Austrian domicile (up to 50%)

Faculty travel budget of 1500 per year plus additional department funds if needed.

Training and coaching: You will have full access to the extensive training and development program offered by the University of Vienna, one of the largest and oldest universities in Europe.

Inspiring and supportive working atmosphere: You will be part of an inspiring international team in a department that was completely overhauled in 2020 with three new chairs and excellent research facilities including department IT infrastructure and personnel.

Applications via our job portal should include:

• Letter of motivation including a statement of research interests and if applicable a research plan
• Curriculum vitae including a list of publications
• Names and contact details of two persons serving as references