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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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Midlands Graduate School Doctoral Training Partnership; | Birmingham, England | United Kingdom | 6 days ago
industrial policy. Evidence will be generated using firm-level data and ownership information on UK multinationals and their subsidiaries. The successful candidate will contribute to a growing field with
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Midlands Graduate School Doctoral Training Partnership; | Loughborough, England | United Kingdom | 12 days ago
for teachers. The project builds on Numeralis, an adaptive screening instrument comprising cognitive and mathematics tasks. The project combines secondary data analysis, large-scale pupil screening
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will be considered. Other scholarships at QUT may require you to complete a separate application form. For further information, view our scholarships . What happens next? Due to the large volume
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to study information or people Site content Qualifications & courses Scholarships & awards Search Māori @ Massey International students Library Portal Stream Alumni Apply to study Māori @ Massey
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Midlands Graduate School Doctoral Training Partnership | Loughborough, England | United Kingdom | 11 days ago
the wellbeing equity gap related to housing inequalities? Methodological approach The project suggests a mixed-methods design. Quantitatively, the student will work with large and complex datasets — including
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19 Jan 2026 Job Information Organisation/Company Forschungszentrum Jülich Research Field All Researcher Profile First Stage Researcher (R1) Application Deadline 19 Jan 2038 - 03:14 (UTC) Country
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network approaches for stress prediction in arterial walls and plaque. Another part of the project is exploring the use of large language models to support neural network design and data preprocessing
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Science Center has an opening for a graduate student researcher in Mathematical Optimization for large-scale power systems planning. They will deploy developed optimization algorithms on DOE high
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-time, large-scale data demands of IIoT and lack sustainability considerations, such as energy efficiency. This research proposes a sustainable, high-performance IDS that leverages digital twin technology