122 parallel-and-distributed-computing-phd-"Meta"-"Meta" positions at UNIVERSITY OF VIENNA in United Kingdom
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to analyze and reconstitute complex biological systems across different scales. Candidates should have a proven track record in biology, biophysics, or computational science. Your research proposal should be
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applications. In teaching, the applicant will be involved, inter alia, in the education of fundamentals in mathematics in all study programs of the faculty, esp. in the Master program Business Analytics. The
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an innovative perspective on research-led museums studies within the art history program. Your responsibilities include: developing and leading a dynamic research agenda in museum studies; designing and teaching
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intercultural philosophical discourse are a prerequisite for a successful application. We are seeking to appoint an excellent candidate who will contribute significantly to the profile and teaching program in
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://www.soz.univie.ac.at/en/ Your academic profile: Doctoral degree/PhD Two years of international research experience during or after doctoral studies Outstanding research achievements, excellent publication and funding
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have access to high performance computing facilities. The faculty runs the Vienna International School of Earth and Space Science (VISESS), a well-recognized doctoral school providing a platform for
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: “Biomolecules for a Healthy Lifespan,” “Computational Life Sciences,” and “Innovation in Drug Research.” The tenure-track professorship will be located at the intersection of these areas and will contribute
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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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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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Biochemical Network Analysis group, led by Jürgen Zanghellini . The team focuses on mathematical modeling, artificial intelligence, and high-performance computing to study metabolic networks and optimize