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, with flexibility to choose their approach and methods within the project’s overarching aims. They will prepare scientific publications and engage actively in collaboration within the project’s
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disorders) with the aim to clinically validate the methods and promote their translation to healthcare. The positions are funded from Research Council of Finland project 'VR2Real: Precision diagnostics
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will design and implement novel computer vision and machine learning methods for “sensorized” cameras that extract medically relevant features without transmitting raw video. You will evaluate algorithms
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for green hydrogen continues to rise, the high energy demands associated with conventional methods like electrolysis highlight the need for alternative approaches. Photocatalysis, leveraging solar energy for
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research profile in inverse problems and computational mathematics. About the job This project focuses on developing advanced methods for uncertainty quantification in inverse problems, i.e., mathematical
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Has demonstrated expertise in conducting dietary trials either in humans or in animals, using molecular biology methods on biological samples, and analysing clinical trial data using advanced
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computing in large-scale omics data analysis. Your work will focus on method development and their application to biomedical research questions. Key responsibilities include: analyzing and modeling large
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, the candidate should be open to interdisciplinary collaboration and comfortable with working in multi-method research contexts. Additionally, due to the specific framing of these positions, researchers accepted
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molecular biology methods on biological samples, and analysing clinical trial data using advanced bioinformatics tools (preferably using R) Has solid track record and strong scientific drive Ability to work
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the entire population. The project utilises advanced statistical methods such as multilevel models (mixed models), fixed-effects models, cluster analysis, and sequence analysis. The selected researcher is