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University Assistant (post doc) at the Department of Astrophysics
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 (post doc)
at the Department of Astrophysics
Reference number: 9908
We offer a postdoctoral research position on stellar dynamical archeology with nearby galaxies in the group of Prof. Glenn van de Ven in the Department of Astrophysics. The starting date can be as early as 1 March 2020 and the duration is for 4 years.
We seek an outstanding candidate to work in our research team to further develop and apply our novel population-dynamical models to nearby galaxies observed with integral-field unit spectrographs such as MUSE at ESO's Very Large Telescope. By fitting simultaneously the extracted stellar motions and population properties, the aim is to uncover the luminous and dark matter distribution of these galaxies as well as to unravel their formation history.
You will have the opportunity to work within a dedicated team on forefront science, while profiting from the international environment in the Department of Astrophysics within the lively city of Vienna. Our team has privileged access to the Vienna Scientific Cluster super-computing facility. You have access to ESO's world-leading observing facilities and opportunities to get involved with instrument projects. You participate in teaching and supervision of students. Generous financial support is available to attend international meetings as well as to invite science collaborators.
Active participation in research, teaching and administration. This involves
Developing and strengthening the independent research profile;
Involvement in research projects / research studies;
International publications and presentations;
Responsibility for project applications and the acquisition of third-party funding;
Independent teaching of courses as defined by the collective agreement;
Supervision of students;
Participation in evaluation measures and quality assurance;
Involvement in the department administration as well as in teaching and research administration
Doctoral/PhD degree in astronomy / astrophysics, or in computer science / applied mathematics;
Excellent command of written and spoken English;
Excellent communication skills;
Very good programming skills;
Good research profile;
Ability to work in a team
The position will involve the extension and synergy of our Schwarzschild orbit-superposition and discrete chemo-dynamical numerical codes. The combination of computationally intensive stellar population and dynamical models applied to state-of-the-art spectroscopic data will require novel optimisation algorithms and efficient programming. Therefore, it is an asset if the successful candidate has:
Experience in stellar dynamical modelling;
Experience in stellar population modelling;
Experience in stellar spectroscopy
Further desirable qualifications are:
Experience in teaching and training;
Experience in (co-)supervising students;
Experience in (co-)organising events
Your application should be a single PDF file that includes a letter of motivation, a curriculum vitae (with a list of publications and presentations), and a statement of research interests (maximum of two pages). You should also arrange for 3 persons to send a recommendation letter to firstname.lastname@example.org (mentioning reference number 9908) by the closing date.
Main research field
Special research fields
Type of computer skills
Specified computer skills
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 30.11.2019, mentioning reference number 9908.
For further information please contact van de Ven, Petrus Martinus +43-1-4277-53806.
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.