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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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focused on: Developing gene therapy approaches for inherited retinal diseases. Designing and optimising CRISPR-based gene editing strategies, including base editing and prime editing. Generating and
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for internationally recruited employees with their transition to work and life in Finland. For more on the University of Helsinki as an employer, please see https://www.helsinki.fi/en/about-us/careers
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goals. Our other research directions of interest include privacy of AI models trained on health data as well as training AI models on health data across national borders. Key responsibilities Design
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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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, or innovation studies). This requirement must be met by beginning of the employment. Has demonstrated expertise in qualitative methods, preferably in qualitative comparative analysis Has a solid track record and
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questions where the notion of risk can be utilized, such as ‘can knowledge be understood in terms of risk?’, ‘are closure principles compatible with an anti-risk conception of knowledge and justification