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will work with the PI and lab members to apply newly developed tools and leverage unpublished datasets to design and execute rigorous functional studies in vitro and in vivo. In addition to developing
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of the appointed researcher is - jointly with the research team - to design and conduct quantitative research, mostly on longitudinal register-based data on autoimmune diseases. Additionally, the researcher is
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, proteins) in the nanopores such as: Design and fabricate glass nanopipettes and characterise them by biomolecule translocation; Design, fabricate and characterize plasmonic nanopores on the nanopipettes with
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participation over the short, medium and longer-term. Essential criteria: Excellent social survey research skills, including the design and administration of surveys to multiple populations Excellent skills in
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of Innovation in Society and Ethics and Wellbeing. The positions are fully funded by the programme. Please see NOVEL’s website for a description of the research areas. Postdoctoral researchers will be working
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. Flexibility to design your own line of inquiry within colour, immunity, performance, and eco-genomics. Possibilities for collaboration within Finland and abroad. The University of Helsinki offers comprehensive
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and experience in crop physiology or related field. A successful candidate should be able to Design, conduct, and publish research within the scope of the project Contribute to undergraduate and
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
predictive models for complex multi-physics dynamical systems as well as towards designing observer-based state estimators from output timeseries data measurements. The research also involves development
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synthesis methods for the Abstraction and Reasoning Corpus (ARC) challenge . ARC is a benchmark designed to measure an AI system's ability to efficiently acquire new skills outside its training data
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design and analyse separation processes, develop data-driven or AI-assisted tools, or generate high-quality experimental data that supports method development, modelling, and machine learning. You will