326 structures-"https:" "https:" "https:" "https:" "https:" "IMT Atlantique" Fellowship positions in Norway
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be found here: https://uit.no/staffmobility UiT via Unsplash UiT How to apply Please note that the application will only be assessed based on the information submitted by the application deadline via
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of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows: the average grade point
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exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows: The average grade point for courses included in
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countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows: the average grade point for courses
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structures for efficient CO2-capture and storage. The postdoc will use atomistic modelling with both force field and ab initio methods to study various systems of surface adsorbed aromatic macrocycles or also
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invites applicants for a PhD Fellowship in Resilient Bridge Infrastructures at the Faculty of Science and Technology, Department of Mechanical and Structural Engineering and Materials Science. The position
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oral and written communication skills in English English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd
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research infrastructure, hosted at the USIT TSD service (https://www.uio.no/english/services/it/research/sensitive-data/index.html). The main purpose of the fellowship is to qualify researchers for work in
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leader will be Professor Jonathan Robert Whitlock (read more about the group at: https://www.whitlocklab.org/). About the project The successful candidate will perform large-scale neural recordings in
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University of Stavanger invites applicants for a PhD Fellowship in Surrogate Modelling of Fluid Flows using Deep Learning at the Faculty of Science and Technology, Department of Mechanical and Structural