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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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and students from all over the world. Our research spans from evolutionary ecology and genetics to ecosystem studies. Learn more at www.ieg.uu.se . We are now looking for a PhD student in evolutionary
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genetics to ecosystem studies. Learn more at www.ieg.uu.se . We are now looking for a PhD student in evolutionary genomics, with specific focus on diversity and evolution on lichen-associated basidiomycetes
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place great importance on personal suitability as well as motivation and the ability to independently conduct research studies. Previous experience in modeling and simulation, machine learning/AI, high
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implementation is a plus, but not a requirement as we have the expertise to teach these as part of the project. A higher degree such as a PhD, or progress in a PhD programme is a merit. About the employment
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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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to independently analyse data and to develop scientific texts on a scientific basis Knowledge of advanced statistical and machine learning techniques Experience in developing data visualization. Additional
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robotics and human-robot interaction (Ginevra Castellano and Katie Winkle), LLMs and deep learning (Ekta Vats), and privacy and cybersecurity (Boel Nelson). Duties The successful candidate will work with
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learning A high level of proficiency in English (reading, writing) Knowledge in Python 3.X, since most programme code is written in this and the researcher will have to contribute to this code base Ability
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abilities necessary to develop within and acquire the doctoral education. Additional qualifications We are looking for a highly driven person, who shows clear signs to perform research work independently and