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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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completed during the first two years of employment. Documented ability to teach in Swedish or Englishis a requirement unless special reasons prevail. Personal capabilities necessary to carry out fully
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subject. Completed project in single cell analysis of cell painting data. Experience with multivariate methods, supervised and unsupervised machine learning including deep neural networks and self
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doctoral students active on both campuses. Learn more about the Department here: https://www.uu.se/institution/arkeologi-och-antik-historia . Center for the Human Past The CHP is a pioneering initiative that
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circumstances apply, this training for teachers in higher education may be completed during the first two years of employment. Documented ability to teach in Swedish or English is a requirement unless special
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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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applies finite-field density functional theory (DFT)-based and machine learning (ML)-accelerated molecular dynamics (MD) simulations recently developed and applied in the TeC group at Uppsala (https://tec