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Field
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the development of new algorithms for processing, analysis and inversion of active and passive seismic data and the application of these algorithms to field data. Student type Future Students Faculties and centres
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the autumn of 2025 or as agreed. Project description This doctoral position has a special focus on sustainable data cultures, algorithmic decision-making and AI solutions within municipal companies
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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programming Creating their own mechanical designs, implement and test them accordingly, Implementation of control algorithms on physical experiments. In addition, the candidates are expected to contribute with
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philosophiae doctor (ph.d.) and philosophiae doctor (ph.d.) in artistic development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection
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embedded within the department Law & Markets, home of a vibrant and diverse academic community. The overarching mission of the department Law & Markets is to develop and deliver cutting-edge, high-quality
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. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop machine learning surrogates of wind energy systems. As newer
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and developmental biology, mechanobiology, stem cells and differentiation, network reconstruction and systems biology, proteomics, genomics, metabolomics, sequencing and algorithms, computational
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skills and be interested in developing a collaborative program of applied research in robotics. For example, this may include sensor development, applied robotic perception, algorithm development, or other
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population