20 parallel-processing-bioinformatics uni jobs at AIT Austrian Institute of Technology
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decision-making processes in an open, agile organizational structure. Close cooperation with leading national and international partners as well as access to unique AI and HPC infrastructure. Comprehensive
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work through innovation. We help our partners by making technical systems more robust, reliable, flexible and easy to use. At the same time, we increase the resource efficiency of industrial processes by
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the agricultural or food sector Knowledge and experience in technological processes Excellent written and spoken German and English skills Strong team spirit, commitment, a responsible approach to work, as
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Scientist (f/m/d) for System Transition Modelling & Policy (Full time / Part-Time: 25+ hours / week)
the question of how transition processes and policies can be designed to best contribute to the solution of major societal challenges. Therefore, our scientists place a research focus on the design and analysis
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of industrial processes by reducing waste, product failures and emissions. The automation of work machines, such as cranes and forklift trucks, is a strategic research goal at VAC. In the future, these machines
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qualifications as an Ingenious Partner: Completed university degree, preferably in computer science, electrical engineering, computer engineering, mathematics, physics or similar (minimum BSc. degree) Good
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qualifications as an Ingenious Partner: Completed university degree, preferably in computer science, electrical engineering, computer engineering, mathematics, physics or similar Knowledge in at least one area
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cities and their stakeholders in cross-sectoral transformation processes, combining expertise particularly in the areas of climate, energy, mobility, and urban planning. With the goal of creating climate
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and validating the dependability of software and systems – during conception, development, certification and operation. Additionally, we also focus on risk management, dealing with dependencies within
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and testing, test design with DoE or ML methods, battery cell-to-system integration, battery monitoring and control (including sensors’ data processing). The candidate is expected to describe in his/her