159 parallel-and-distributed-computing-"LIST" positions at UNIVERSITY OF VIENNA in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
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
-
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
-
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
-
current cooperation partners complete list of acquired third-party funding and, if applicable, of inventions/patents list of most important scientific talks (max. 10) teaching and mentoring supervision
-
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
-
: “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
-
. publish internationally and give lectures. apply for projects and raise third-party funds. teach courses in the master's programme "Philosophy and Economics" (within the scope of the provisions
-
that analyses the interactions of science, technology, and society. The department offers the English language master program 'Science, Technology, Society', as well as a number of course formats for
-
personality to the team! It is that easy to apply: With your letter of motivation With your scientific curriculum vitae / letter of intent With your list of publications With your summary of research interests
-
. program and will work on the development and analysis of statistical methods for machine learning, particularly in the context of high-dimensional models and with a particular focus on methods such as