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will join a research group working on longitudinal models of multiple chronic diseases across the life course. The postdoctoral researcher will contribute to building and evaluating machine learning
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investigates how electricity markets must be designed, and how demand-side flexibility must be mobilised, for a power system dominated by variable renewable generation to remain reliable and affordable
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. Employment starts as soon as possible. Position description The postdoctoral position funded by the Research Council of Finland aims to design closed-loop dissolution/activation laboratory and scaled-up
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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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behaviours. NATURETIME aims to generate actionable knowledge to inform the design of cities and other living environments, thereby improving human time-perception regulation, boosting well-being, and
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knowledge that can inform the design of cities and other living environments in a manner that improves human time perception regulation, boosts well-being, and stimulates the positive and sustainable
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an advantage skills in electronics, e.g., RF electronics, MRI coil design, gradient coil design, etc. programming skills with MATLAB, C/C++ or Python skills and experience in manufacturing methods, such as 3-D
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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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. Responsibilities: Design, develop, and implement state-of-the-art foundation health models and clinical reasoning algorithms. Collaborate closely with top-tier partner universities and clinical/industrial partners