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Wallenberg National Program for Data-Driven Life Science (DDLS), coordinated by SciLifeLab, aims to recruit and train the next-generation of data-driven life scientists and to create globally leading
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of the Architecture Programme, or in the Master's Programme in Architecture and Urban Design at the Umeå School of Architecture Have good knowledge in architectural visual representation and modelling in both 2D and
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. Project description: DDLS Fellows Program Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular
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of data-driven life science and includes access to a formidable package of resources. Project description: DDLS Fellows Program Data-driven life science (DDLS) uses data, computational methods and
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development. Work responsibilities The candidate will lead a multidisciplinary research program investigating the genotoxic and epigenetic effects of NPs. Responsibilities include developing mutagenesis assays
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General description of the DDLS Fellows programme Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels
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Transformation and as a Transformative Power (ProTest), funded by Horizon Europe – the European Union’s key funding programme for research and innovation. The project aims to analyse the context, current state
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independence, and how the applicant, through their experience and skills, is deemed to have the abilities necessary for successfully completing the third cycle programme. Terms of employment Only those admitted
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consortium, would be advantageous. This, in particular, includes coordination of international university networks and exchange programmes within Europe, including those outside the ERASMUS programme, such as
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of large amounts of imaging data Communicate with other data generating platforms within the SciLifeLabs Integrated Data Service program Collaborate with national high-performance computing (HPC) resources