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University Assistant (post doc) at the Department of Structural and Computational Biology
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 01.07.2020 of a
University Assistant (post doc)
at the Department of Structural and Computational Biology
Reference number: 10806
The Center for Integrative Bioinformatics Vienna (CIBIV) headed by Prof. Arndt von Haeseler at the University of Vienna seeks an experienced and highly motivated Postdoc in the area of phylogenetic inference.
You will join a team working in the field of phylogenetic inference, statistical models and maximum likelihood methods. A special focus is the development of efficient algorithms and high performance computing for big phylogenomic data analysis. The preferred candidate has a proven ability to independently design and implement cutting-edge computational methods for popular phylogenetic software tools. Experience with handling large datasets is required. Experience in next-generation sequence data analysis is a plus.
The candidate is further expected to be willing to teach and is able to supervise students. An extensive teaching experience is therefore expected. The position is also involved with international collaborations.
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
- Preparing / writing a (publication-ready) habilitation thesis
- 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 degree/PhD degree - Professional competence Training in Bioinformatics with focus on phylogenetic inference - Methodological competence Proven competence of developing methods for maximum likelihood and/or Bayesian phylogenetic software tools - Preferred programming experience with Java, R and C++ - Experience working with large sequence datasets - Didactic competence Experience with course organization, teaching and assignments/homework preparation - High ability to express yourself both orally and in writing - Excellent command of written and spoken English - IT user skills - Ability to work both independently and in a team
- In addition, we expect the successful candidate to have: Teaching experience / experience of working with e-learning - Experience of working on research projects - Publications in renowned, subject-relevant media (peer-reviewed, depending on the professional standards) - International presentation experience Desirable qualifications are - Knowledge of university processes and structures - Experience abroad - Experience of supervising students
- 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 / of the intended habilitation project (if applicable) - Contact details of people who could provide a letter of reference
Main research field
Special research fields
Mathematics, Computer Sciences
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 15.06.2020, mentioning reference number 10806.
For further information please contact Gruber, Iris +43-1-4277-74320.
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.