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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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, 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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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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PhD degree in economics with broad experience in conflict research. The PhD degree needs to be obtained by the time of the decision of employment Excellent skills in quantitative methodology and machine
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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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. This qualitative data will be digitised, made machine-readable and processed using modern qualitative data processing techniques. Project qualifications: Relevant background is a degree in economic history