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- University of Oslo
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in statistical modelling is an advantage. The project involves close interdisciplinary collaboration between statisticians and NLP researchers at Integreat. The position is also affiliated with
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). High skills in statistics and the application modern epidemiological methods, as well as causal inference methods High programming skills in R or STATA. Fluent oral and written communication skills in
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synthetic data generators that obtain both good utility and protection of privacy, through tailored model approximation, as well as new measures of privacy and fairness to be used for assessing properties
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-AI systems. You will gain skills in custom chip design, artificial neural networks and edge-AI system implementation. The work combines circuit-level simulation, system modeling, and in-silicon
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work on adapting or developing marine foundation models. Self-supervised learning and active learning are also possible research topics. You can also focus on challenges related to modelling physics
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in the μ-opioid receptor. The PhD candidate will: • generate high-resolution models of wild-type and R181C mutant μ-opioid receptor based on existing crystallographic data and perform molecular
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learning methods for generating complex structures for generation of virus capsids and therapeutic proteins for gene therapy. The project will involve both physics-based forward modeling of protein
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candidate to develop Machine Learning models and frameworks for time series analysis, aimed at understanding how the human brain encodes information. This cross-disciplinary project is a high-level
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of hypothermia with important medical implications. To study this, the Ph.D. candidate will use mammalian cells, organoids, and animal models, and employ a range of approaches, including cell culture systems
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, which will also be involved in CH-CYCLE. The postdoctoral research fellow will conduct research on topics such as: Model studies of CO2 versus ethene hydrogenation activity of candidate catalysts