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develop and evaluate semi automated machine learning techniques for content analysis adapted to handwritten documents and early printed books. These approaches will build upon existing optical character
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retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Position Description Advertised Job Summary Teaching duties will
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countermeasures, and cloud security concepts. Candidates should possess a PhD or equivalent experience, ideally in computer or information science and preferably with a track record in the delivery of study modules
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of quantum mechanics and statistical mechanics. The Computational Biochemistry group consists currently of eight coworkers and combines quantum chemistry, statistical mechanics and machine learning with
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, energy consumption, and packet loss. The use of distributed machine learning provides a relevant solution to mitigate the lack of communication reliability [3][4]. This PhD proposes to guide the learning
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integrated onto drone platforms engineered by project partners, with the objective of assessing the structural integrity of concrete façades. Objectives The objective of this PhD thesis is to develop a Machine
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or more of the following areas: AI and machine learning, natural language processing, large language models (LLM), experience in designing prompts, fine-tuning LLMs, or distributed systems. Good knowledge
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Torbein Kvil Gamst 26th April 2026 Languages English English English Faculty of Science and Technology Postdoctoral Research Fellow in Machine Learning Apply for this job See advertisement
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of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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recrystallization and control nucleation for biomedical applications in e.g. heart and kidney cryopreservation. Where to apply Website https://www.academictransfer.com/en/jobs/359905/phd-in-de-novo-design-of-ice-bi