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Field
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and vegetation development. This PhD project is part of a larger interdisciplinary research initiative aiming to enable a transition towards more data-driven and environmentally responsible maintenance
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and analysis of dedicated algorithms for training analog circuits directly from data. In this PhD project, you will develop a novel system-theoretic framework for learning in analog circuits and
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of recruitment. Must fulfil the conditions for enrolment to PhD programme at the host institution. For details about the criteria, please refer to detailed description of positions found at https://desire-msca.eu
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. For further information about a specific subject see general curricula for the Board of the faculty of science and technology Further information Employment as a PhD student is limited to 4 years
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information Employment as a PhD student is limited to 4 years, teaching and other department duties may be added with max 20%. Placement: Luleå. Starting: According to agreement. For further information please
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field data, experimental data, and field experiments. Salary is $70,500 annually, plus benefits. Expected start date is mid-June 2027. For examples of our research, see our faculty pages: https
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combinations that support the creation of innovative and sustainable food products. Another example is using large language model (LLM) tools to automatically extract and structure fragmented information from
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sits at the intersection of AI Safety and Data-Centric AI. We aim to make large-scale ML more reliable, transparent, and aligned with human values. We are specifically interested in: Data-centric AI
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knowledge for a better world. You will find more information about working at NTNU and the application process here. About the position Long term management of large scale computing infrastructures requires
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knowledge security. Please do not contact us for unsolicited services. Where to apply Website https://www.academictransfer.com/en/jobs/364056/phd-position-quantum-torsional-… Requirements Additional