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initiated to explore how machine learning and the combination of different types of data (optical and electrical) can be utilized to improve decisions during on-going experiments as well as its potential
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large family of membrane proteins involved in numerous physiological processes. By leveraging machine-learning enhanced virtual screening, the PhD student will be able to perform searches for ligands in
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. Intrusion Detection Systems (IDS) are critical components of an effective IoT cybersecurity defense strategy and machine learning plays a pivotal role in intrusion detection by learning from past and
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, image analysis and machine learning, mathematics or similar, or have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including an independent project worth
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machine learning methodologies to extract conformational ensembles from single-particle cryo-EM data. The project builds on our recently established (not yet published) software, which machine-learns
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user studies are valued. Experience with large language models and machine learning for human-robot interaction is valued. Rules governing PhD students are set out in the Higher Education Ordinance
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ability to teach in Swedish or English is a requirement unless special reasons prevail. Personal capabilities necessary to carry out fully the duties of the appointment. Assessment Criteria/Ranking
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machine learning are valued. Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines . Application The application must
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successful research and education in these areas - renewable energy sources, electric vehicles, industrial IoT, 5G/6G communication, machine learning and wireless sensor networks as well as smart electronic
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recruitment system. If you have specific questions regarding a course, please contact Hans Rosth. Period 1: 1RT705/1RT003 Advanced Probabilistic Machine Learning 1RT490 Automatic Control I, period 1 and 2 (SVE