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in the research and management of the Computational Materials Discovery group. You supervise and guide students at the bachelor, master and PhD level. You contribute to the teaching activities in
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to the study and teaching of the language and literature of ancient Greece and Rome, including Late Antiquity, as well as the late, medieval, and Neo-Latin language and literature. At the core of the program is
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the successful software package VASP (Vienna ab-initio Simulation Package). Currently, the group consists of two full professors, one associate professor, several postdocs and about 10 PhD and master students
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personality: Master in Computer Science, Applied Mathematics or equivalent qualification with a strong focus on Computer Science with excellent marks. PhD with focus on data mining Strong publication record
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, which means: Developing a third-party funded project to be submitted to a competitive programme (e.g. Marie Curie, FWF individual project, FWF Esprit) Further developing your academic profile through
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tomography and single-photon emission computed tomography. We are a highly interdisciplinary and international team closely working together with colleagues from different medical universities, biomedical
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administrative tasks in research, teaching and administration. This is part of your personality: PhD degree in analytical, biological, food, or computational chemistry, biotechnology or related field Experience in
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measures and quality assurance. This is part of your personality: Must-haves: Completed doctoral/PhD studies in Computer Science Outstanding dissertation Research competence and initiative proven through
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activities (if applicable), Bachelor and Master degree certificates, your certificate of a completed PhD programme (required before the start of the contract) and contact details of 2 persons for reference
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: Department for Structural and Computational Biology at the Max Perutz Labs, a research institute established by the University of Vienna and the Medical University of Vienna. Dedicated to a mechanistic