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in Finland in its area and responsible for the teaching and research in computer science at the University of Helsinki. The main research fields at the department are artificial intelligence, big data
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academic events. The research team operates in English, good oral and written proficiency in English is important. Since a big part of the archival data is in Swedish, ability to read and understand Swedish
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combining large-scale ecological datasets, species trait data, ecological network analyses, and quantitative modelling. The postdoctoral researcher will also coordinate and lead field resurveys of historical
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Ability to curate and integrate large scale biomedical data Experience with workflow management and HPC environments Interest in RNA biology, alternative splicing and computational method development Strong
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, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and
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, implement and benchmark machine learning models for large-scale health datasets consisting of diverse information including structured medical history, demographics, clinical notes, laboratory measurements
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on health data as well as training AI models on health data across national borders. Key responsibilities Design, implement and benchmark machine learning models for large-scale health datasets consisting
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research in computer science at the University of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete
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approaches to large-scale biomedical data. Research topics may include foundation models for longitudinal electronic health records and genomics, multimodal learning integrating health records with molecular
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candidate is expected to develop an independent research programme within this broad scope, focusing on methodological innovation and the application of modern AI approaches to large-scale biomedical data