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theoretical modelling. The project will focus on self-learning active mechanical networks, but will be tailored to align with the interests and expertise of the successful candidate - we will mutually ensure
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related field with a strong quantitative focus. Strong programming skills in Python and demonstrated experience with machine deep learning frameworks (for instance, PyTorch or TensorFlow), preferably
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. – knowledge of computer vision; knowledge of deep learning architectures; – Knowledge of C++, Python, Matlab; – Analog/digital circuits IC design capability; – Testing of electronic devices and systems; FPGA
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sensors capable of characterizing the dynamic state of buildings and their inhabitants. By combining multi-microphone acquisition techniques with state-of-the-art machine learning methods, acoustic sensing
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, or computer science. Core competencies: solid background in quantum many-body physics strong programming skills (Python required, Rust a plus) experience with tensor networks, variational Monte-Carlo, machine learning
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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 We have a vacancy for a PhD candidate in machine learning
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
learning, privacy, security and distributed systems. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2026-10411 Requirements Skills/Qualifications We are looking for a candidate with
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algorithms, and some knowledge of data science and machine learning (through coursework, self-learning, or personal projects). The selected student will work with Ph.D. and master's students to help develop
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goal of your PhD project will be to develop combined X-ray and visible-light imaging technologies and machine learning methods for high-throughput inspection tasks. The work will include the development
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high-resolution mass spectrometry, in vitro pharmacological characterisation of new psychoactive substances, as well as metabolomics and machine learning. As a PhD student, you devote most of your time