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Field
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will help influence how new evidence drives system change, supporting the region’s shift toward a more integrated, equitable, and learning-oriented model of mental health care. You will be part of
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metal dichalcogenides are promising platforms for next-generation quantum and electronic devices, where atomic defects play a crucial role in determining functionality. This project develops a machine
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repair on RNA-DNA hybrids of R-loops using computational modeling and molecular dynamics simulation along with various types of AI tools and machine learning approaches. Temporary Expertise in
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spatial and temporal data analysis using advanced machine learning technologies. The successful candidate will become a part of an interdisciplinary team working to develop machine learning techniques
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to high-performance computing facilities and datasets from laboratory experiments will be provided to support simulation and verification of the resulting model. Replicate and learn a theoretical model for
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, robotics and machine learning, focusing on fundamental aspects as well as on applications in multidisciplinary contexts. This position is part of the DRIVE project, funded by the Research Council of Norway
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processes of the study systems of our collaborators. Core components of the research involve, among others, Bayesian hierarchical modelling, shrinkage methods, machine learning (ML) or dimension reduction
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focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute
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with anxiety and co-occurring learning difficulties. Specific duties include recruiting and scheduling participants, making phone calls, assisting with research study visits, collection of cognitive
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on the development of machine learning algorithms, particularly transfer and adaptive learning, for multimodal wearable biosensing and its translation to rehabilitation and digital health applications. It is co