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This PhD position is part of the WASP-WISE NEST project RAM³ – a multidisciplinary research effort at the intersection of machine learning and materials science. The project brings together PhD
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university research into commercial outcomes. Under this program, PhD students will gain unique skills to focus on impact-driven research. This Project aims to develop a predictive machine learning model
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, which has multiple test machines with GPUs and AI accelerators. The algorithms used can be bound by the available compute power or memory bandwidth in different parts of the program. This information will
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the conditions defined for admission to a PhD programme at NMBU. The applicant must have an academically relevant education corresponding to a five-year master’s degree with a learning outcome
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epidemiology and machine learning. The scholarship will fund course fees up to the value of home fees*, a tax-free stipend of no less than £20,780 per annum), plus additional support for research expenses
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Join us for an exciting and excellent PhD journey! Everyday user behaviour may affect the environmental performance of household appliances, yet it is often overlooked in environmental assessments
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machine learning techniques to predict market behavior and generate alphas Execution. Create strategies to execute on modelling ideas under simulated competition Evaluation. Backtest ideas using historical
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machine learning techniques to predict market behavior and generate alphas Execution. Create strategies to execute on modelling ideas under simulated competition Evaluation. Backtest ideas using historical
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Aerospace Centre (DLR), will conduct research on 20 research topics with 25 PhD candidates within the next years. The following main research goals are pursued by this Center: (1) develop a new set of
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, statistical analysis, and machine learning techniques to predict market behavior and generate alphas Execution. Create strategies to execute on modelling ideas under simulated competition Evaluation. Backtest