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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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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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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
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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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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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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