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Field
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guidance Exciting infrastructures and unique labs, research tools and software The right place for Impact. SnT researchers engage in demand-driven projects. Through our Partnership Programme, we work
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Software Defined Vehicles (SDV). The primary objective is to expand, mature, and industrialize a novel European RISC-V automotive ecosystem that enables next-generation high-performance European automotive
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interaction with the journal (rotating part). The PhD will be conducted in collaboration with Cummins Components and Software (CCS) [Turbochargers Group] who are developing fuel cell turbomachines which use
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, secure digital communication, medical technology, and new analytical methods. We use and develop basic theory, next-generation instrumentation, and software, and aim to make our data publicly accessible
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of Information Technology and Electrical Engineering. Knowledge of fundamentals of C++ programming. Competence in code optimization. Knowledge of hardware/software co-design principles, and computer architectures. Good
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Maintain a mouse colony and establish genetic crosses Maintain detailed experimental records Use standard laboratory software that includes Microsoft Word, Excel, and PowerPoint, GraphPad Prism, SnapGene
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reusable software and data artifacts where relevant. Communicate research outcomes through papers and talks at conferences, workshops, and beyond. Actively collaborate with other researchers in the TRL Lab
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-powered data analysis. Publish reusable software and data artifacts where relevant. Communicate research outcomes through papers and talks at conferences, workshops, and beyond. Actively collaborate with
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development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Familiarity with software such as R or Python Some experience
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-mechanical coupling. Understanding of wellbore and casing behavior under thermal load. Desired skills: Finite Element Analysis software: Abaqus, COMSOL Multiphysics, or ANSYS Python (for data analysis