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perform 3D single-particle tracking and establish pipelines to characterise the particle motion using a combination of established tracking algorithms and machine-learning-based approaches. Additionally
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integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing of grants and
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skills, including proficiency in statistics, scientific programming, and/or modelling. We especially welcome candidates interested in applying AI and machine learning to analyse heritage datasets
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statistics, scientific programming, and/or modelling. We especially welcome candidates interested in applying AI and machine learning to analyse heritage datasets. What we offer: • A stimulating
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, silicon-proven AI/ML accelerator for transmitter error correction (digital predistortion/calibration). Your work will sit at the intersection of machine learning, DSP, and digital IC design, and you will
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, Higgs physics, particle dynamics in the early Universe, collider phenomenology, applications of machine learning to particle phenomenology, and lattice QCD, both within the Standard Model and beyond
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We are looking for a PhD student in Visual Learning and Communication with a focus on interactive visualization, visual learning, science communication, and educational science, formally based
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who could help with general course delivery, project supervision and marking of assessments. The post holder will teach undergraduate and computing modules within the School of Computing and Engineering
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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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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