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new thermoelectric materials using data science and machine learning methods applied to materials, based on expert-reviewed experimental data from the literature and public databases (notably
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3GPP compliant 5G/6G NR NTN OFDM waveforms Develop and analyse signal processing and/or machine learning algorithms for joint channel, delay, Doppler and carrier phase estimation, remote object ranging
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/en/available-jobs/job/294737/phd-research-fellow-in-reinforcement-learning-for-generative-systems-in-physics-at-the-inted-center Where to apply Website https://www.jobbnorge.no/en/available-jobs/job
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which must be advanced courses in computer science, mathematics, AI, machine learning or similar. The applicant is expected to have good knowledge of computer science, mathematics, algorithms, and
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PhD student will expect to develop some experience in developing power systems models using a range of computer languages and tools (e.g. Python, MATLAB, OPNET, etc), ideally for applications involving
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applications for faculty positions in Computer Science. Faculty specialising in data science, machine learning (deep learning, reinforcement learning, multimodal learning), Generative AI, and computer graphics
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, biodiversity monitoring, and climate resilience. The work supports strategic priorities in Environmental Sciences, Software/Cyber. PhD researchers will explore how AI-driven Earth observation, computer vision
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of this PhD is to develop physics-informed neural operator frameworks that embed governing equations and invariants of fluid mechanics directly into learning architectures, enabling real-time, generalizable
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) signal processing, machine/deep-learning and computational linguistics. The team mobilizes them to produce methodologically sound research in response to some of the challenges posed by the nature and
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leaders to develop and promote human-centric technology and social policies. Further information about Lingnan University is available at https://www.ln.edu.hk/ . Applications are now invited for