Universität Wien

University Assistant (post doc)

 
Universität Wien

Published
WorkplaceWien, Wien, Austria
Category
Position

Description

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

Computational and Soft Matter Physics




Reference number : 10393

The Computational and Soft Matter Physics Group at the Faculty of Physics invites applications for a postdoc position (6 years) in the group of Prof. Christoph Dellago. The group develops and uses modern computer simulation techniques combined with analytical theory to study a broad range of condensed matter systems with an emphasis on the statistical mechanics of equilibrium and non-equilibrium processes. Members of the group contribute to the teaching at the Faculty of Physics at all levels from the Bachelor to the Doctoral program. The successful candidate is expected to participate in the research projects of the Dellago Group currently focusing on soft matter, nanoparticles, phase transitions and stochastic thermodynamics. She or he will also contribute to the teaching of the group and take part in other group activities such as the organization of meetings and public outreach. Duration of contract: 6 years

Duration of employment: 6 year/s

Extent of Employment: 40 hours/week Job grading in accordance with collective bargaining agreement : §48 VwGr. B1 lit. b (postdoc) with relevant work experience determining the assignment to a particular salary grade.

Job Description:
  • Participation in research, teaching and administration
  • Lead participation in externally funded research projects (particularly EU and nationally-funded-projects)
  • Presentation of research activities at international meetings
  • Publication of research papers
  • Independet teaching of courses as defined by the collective agreement
  • Supervision of students
  • Assistance in organization of conferences, meetings and symposiums

    Profile:
  • PhD in physics or equivalent qualification
  • Excellent knowledge of statistical mechanics
  • Experience in molecular simulation methods (molecular dynamics and Monte Carlo) and machine learning approaches
  • Publication and teaching experience
  • Excellent writing and communication skills
  • Ability to work in teams
  • Excellent command of written and oral English
  • Knowledge of German is an advantage

    Application documents:
  • Letter of motivation
  • Academic curriculum vitae (including a list of publications, a list of courses and a list of talks given)
  • Description of research interests and research agenda
  • Contact details of three people who could provide a letter of reference

    Research fields:

    Condensed matter ;Theoretical physics;Materials physics;Solid state physics;Statistical physics

    Languages:

    Applications including a letter of motivation (German or English) should be sumbitted via the Job Center to the University of Vienna ( http://jobcenter.?url=univie.ac.at&module=jobs&id=23816" target="_blank" rel="nofollow">univie.ac.at ) no later than 21.02.2020, mentioning reference number 10393.

    For further information please contact Dellago, Christoph +43-1-4277-51260, Rennhofer, Claudia +43-1-4277-51261.

    The University pursues a non-discriminatory employment policy and values equal opportunities, as well as diversity ( http://diversity.?url=univie.ac.at%2F&module=jobs&id=23816" target="_blank" rel="nofollow">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.

    Human Resources and Gender Equality of the University of Vienna
    Reference number: 10393
    E-Mail: jobcenter [at] univie[.]ac[.]at
    Privacy Policy of the University of Vienna

Web

In your application, please refer to myScience.at and reference JobID 23816.


More job offers worldwide on jobs.myScience.org

Related News



This site uses cookies and analysis tools to improve the usability of the site. More information. |