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dynamics simulations and machine learning methods to study the structure and electrochemistry of disordered materials are also encouraged to apply. The project primarily aims to understand the complex
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to the group’s open-source software, and participation in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, computer science
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school, and taking part in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, scientific computing, statistics, physics or a
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experimental studies, mechanistic modelling, time-resolved data analysis, and machine learning to develop and validate predictive models linking process signals to reaction behaviour, progressing from controlled
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PhD students. The research will be conducted in a collaborative and multidisciplinary environment, with close interaction with major industrial and research partners (e.g., Ericsson, Tele2, RISE
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includes the opportunity for three weeks of training in higher education teaching and learning. The postdoctoral fellow will: Develop and maintain harmonized satellite time-series datasets (Landsat and
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themes: (1) how does the inherited migratory program instruct the juvenile on its first journey?, (2) which are the genes that control migratory behaviour and when and where are they expressed? and (3) how
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higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity of further development. You will have particular
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
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Institutet our overall aim is to uncover fundamental features of normal and leukemic stem cell biology that can instruct new strategies for clinical surveillance and treatment in hematologic malignancies. Your