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theses in the discipline within the Bachelor's Programme in Agricultural Sciences and the Master's Programme in Agricultural Sciences (https://www.helsinki.fi/en/degree-programmes/maataloustieteiden
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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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?’, ‘what kind of structural properties does an anti-risk epistemology predict for knowledge?’, ‘do iterations of knowledge accumulate risk?’, ‘should disinformation be understood as information that incurs
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The University of Helsinki (https://www.helsinki.fi/en ), founded in 1640, is one of the world’s leading universities for multidisciplinary research. The university has an international academic
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the formal admission requirements for PhD studies: https://www.hanken.fi/en/apply/application/phd-programme/attachments . A Master’s degree is required. Please ensure that all required attachments
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activities in one of the following pillars: Pretraining Foundation Health Model: Leading the design and scaling of pretraining pipelines on nationwide health databases and structured longitudinal electronic
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: Researching and building training pipelines for foundation models trained on nationwide health databases and structured longitudinal electronic health records. Medical Reasoning and Grounding: Developing
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integrates materials chemistry, formulation, and interfacial analysis with electrochemical characterization, supported by advanced characterization techniques, to elucidate structure–processing–performance
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of Helsinki, Finland working in the research groups of Prof. Craig Primmer and Dr. Tutku Aykanat (http://www.helsinki.fi/evolution-conservation-and-genomics ) as a part of several related research consortia
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of diverse information including structured medical history, demographics, clinical notes, laboratory measurements, omics and genetics. Collaborate closely with other team members, and national/ international