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information can be found here: https://www.ntnu.edu/mai . Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research of good quality within the framework described
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information can be found here: https://www.ntnu.edu/mai Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research of good quality within the framework described above
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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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numerically implements the newly derived theoretical frameworks using fundamental computer programming languages. The numerical solver will leverage existing modules (by then) developed from the ‘OceanCoupling
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. The post-doctoral researcher will have the possibility to perform basic research on human-AI interaction and contribute to ongoing research activities in AI and Human-Computer Interaction. The candidate is
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after employment. Required selection criteria You must have a relevant Master's degree in Reliability, Availability, Maintainability, and Safety (RAMS) or Cybernetics or Computer/Information Science with
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equivalent education in climate dynamics, meteorology, oceanography, applied mathematics, physics, computer/data science or related fields or must have submitted his/her master's thesis for assessment prior
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networks, computer science or equivalent, with a strong background on theoretical and applied ML/AI. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained
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, a Norwegian Centre of Excellence dedicated to the development and application of advanced computer simulations, including AI-based methods. The project associated with this position aims to take
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methods will be advantageous: Microbiological techniques, as well as computer-based analysis Molecular biology techniques Analysis of high-throughput datasets (DNA seq, microbiological data, competitive