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- Midlands Graduate School Doctoral Training Partnership;
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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 | 4 days ago
central to effective public-health policy and pandemic preparedness. This PhD project lies at the intersection of economic epidemiology, political economy, and data-driven analysis. It will develop economic
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Midlands Graduate School Doctoral Training Partnership; | Birmingham, England | United Kingdom | 4 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 | 10 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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Posting Title Graduate PhD Student Intern (Summer) – Mathematical Optimization . Location CO - Golden . Position Type Intern (Fixed Term) . Hours Per Week 40 . Working at NLR NLR is located
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Midlands Graduate School Doctoral Training Partnership | Warwick, England | United Kingdom | 17 days ago
recovery or resilience? The PhD candidate will be expected to work with large-scale longitudinal and administrative datasets, such as the Millennium Cohort Study (MCS) and Longitudinal Education Outcomes
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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
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Infrastructure? No Offer Description Work group: IBG-4 - Bioinformatik Area of research: PHD Thesis Job description: Your Job: Develop methods and workflows to construct robust co-regulation networks from large
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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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on the BMI website: go.fzj.de/bmi.tvoed.entgelt Further information on doctoral degrees at Forschungszentrum Jülich (including its various branch offices) is available at www.fz-juelich.de/en/careers/phd We