433 data-"https:" "https:" "https:" "https:" "https:" "https:" "University of New Hampshire" Postdoctoral research jobs in United Kingdom
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relevant PhD/DPhil or be near completion, together with relevant experience in the field. Informal enquiries may be addressed to Prof Natalia Ares (email: natalia.ares@eng.ox.ac.uk) For more information
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for all. Find out more about the benefits of working at the University and what it is like to live and work in the Durham area on our Why Join Us? - Information Page The Role and Department The Department
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and to view further information about the role, please click 'Apply' above. Please notice that if you have not received any news from us 1 month after the closing date you should consider
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approaches to reducing HFSS consumption influence UPF intake. You will conduct quantitative analysis of existing data to explore the equity and effectiveness of diverse population interventions on UPF
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collaborators at DU ES and the industrial partner WLL. Experience conducting quantitative research including fracture data collection, management, and analysis is essential. Excellent initiative, flexibility in
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to develop their scientific career and have an impact in the cell invasion and cancer fields. More information about our research can be found here: www.bci.qmul.ac.uk/staff/dr-pedro-monteiro About You Our
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communication skills, including the ability to write scientific text well, present data clearly, and communicate science effectively. Applications for this vacancy should be made online and you will need
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, planning and organising analysis and research, with attention to detail are also required. You will have excellent communication skills, including the ability to write scientific text well, present data
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About the Role This is an opportunity to work as part of the team and project “Uncertainty Aware Data Attribution Of Vision-Language Models” funded by Huawei Technologies Duesseldorf GmbH, led by Dr
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of reproducing aerodynamic loads in real time for physical experiments. The project combines numerical modelling, data-driven methods, and laboratory experimentation to advance next-generation real-time hybrid