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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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I work on the study of massive and supermassive stars (10-100,000 solar masses); the first generations of stars in the universe (Pop III stars); evolution of rotating massive stars and the spin
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University but includes satellites at several other Danish and international research institutions. CORC strives to develop knowledge and scalable technology that can be used to capture and recycle carbon
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– depending on the successful candidate’s background and interests. Your tasks: Develop new exact and approximation algorithms and perform complexity analyses for optimization problems on (temporal) graphs
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are suitable. The aims of this project are to Review operating characteristics proposed for rare disease trials Develop novel Bayesian operating characteristics for different types of rare disease trials Apply
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bioinformatic skills to predict the evolution of rare diseases? FSHD is a rare neuromuscular disorder. No approved treatment is currently available. Slow and variable disease progression complicate trial design
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Project details Early detection of cognitive decline allows identification of those at high risk of developing dementia when medical treatments may be effective in preventing disease onset. Our
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digitalisation. To achieve our goals, we rely on our specific research, development and technology competencies, which are the basis of our commitment to excellence in all areas. With our open culture
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that addresses large and complex issues and develops new analytical tools. That’s why the WIFORCE Research School, part of the Wallenberg Initiatives in Forest Research (https://www.slu.se/WIFORCE/en
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Digital Sky Survey" "Data-driven methods for stellar spectroscopy" "Chemical abundances in star clusters using Korg, the first spectral synthesis code developed in two decades" web page For further details