185 parallel-and-distributed-computing-phd positions at University of Vienna in Austria
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computing facilities. The faculty runs the Vienna International School of Earth and Space Science (VISESS), a well-recognized doctoral school providing a platform for interdisciplinary research, transferable
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certificate of a completed PhD programme (required before the start of the contract) and contact details of 2 persons for reference, to be sent directly to olga.mula.hernandez@univie.ac.at referencing the job
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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
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intelligence, and high-performance computing to study metabolic networks and optimize microbes for biotechnological applications. The PhD project aims to predict the optimal compartmentalization of a production
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information and to submit your application, see: https://visess.univie.ac.at/phd-programme/funding-possibilities/visess-completion-grants/ . Your future tasks: You actively participate in research, teaching
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computational software development. You enjoy working in a team where you contribute your expertise and skill set to deliver an ambitious research vision and where you can contribute to the training of PhD and
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flexible work environment, a competitive salary, and opportunities for professional growth in an international, dynamic setting. Key Responsibilities: Develop and complete a PhD dissertation on geohazard
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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
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well as the late, medieval, and Neo-Latin language and literature. At the core of the program is a thorough education in Greek and Latin that enables critical evaluation of historical texts, along with
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Mathematics or equivalent qualification with a strong focus on Computer Science with excellent marks. PhD with focus on data mining Strong publication record Leadership abilities to supervise students and PhD