130 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "https:" "J" positions at University of Vienna
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Biophysical Chemistry. Successful candidates will join a structured doctoral programme offering first-class supervision, vibrant research networks, and opportunities to publish, teach, and engage
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personality: Female applicants (inclusive understanding of gender identities within the legal framework and the University’s Equality Plan: https://satzung.univie.ac.at/alle-weiteren-satzungsinhalte
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of gender identities within the legal framework and the University’s Equality Plan: https://satzung.univie.ac.at/alle-weiteren-satzungsinhalte/frauenfoerderungs-und-gleichstellungsplan/ PhD awarded by
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(inclusive understanding of gender identities within the legal framework and the University’s Equality Plan: https://satzung.univie.ac.at/alle-weiteren-satzungsinhalte/frauenfoerderungs-und-gleichstellungsplan
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of gender identities within the legal framework and the University’s Equality Plan: https://satzung.univie.ac.at/alle-weiteren-satzungsinhalte/frauenfoerderungs-und-gleichstellungsplan/ PhD awarded by
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and Master), and in two doctoral programs. Details on the department can be access on http://geographie.univie.ac.at/en/home/ . Your personal sphere of influence: The position is assigned to the working
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(written and spoken) are essential. What we offer: The successful candidate will be embedded in the working group of Dagmar Woebken https://dome.univie.ac.at/woebken at CeMESS – an internationally leading
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computer science or a comparable degree program with a clear focus on computer science Very good English language skills. Very good programming skills, mastery of Python programming language Strong ability to work
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should also actively contribute to and collaborate with the CRC TACO, https://sfb-taco.at/ a joint research project funded by the Austrian Science Fund. Qualification: Applicants have outstanding
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programming paradigms, languages, compilers, and software and hardware infrastructures for scientific computing to support users in the process of solving increasingly complex compute- and data-intensive