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Midlands Graduate School Doctoral Training Partnership | Warwick, England | United Kingdom | 11 days ago
early task will be a structured review of data availability and linkage possibilities to refine research questions and ensure feasibility. The project will employ relevant advanced quantitative techniques
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Infrastructure? No Offer Description No. 1 scholarship grant for technological training activities at INFN Structure of Pisa for the following research topic: “Application of artificial intelligence for control
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? No Offer Description No. 1 scholarship grant for technological training at INFN Structure of Padova for the following research topic (on the following activity): “Development and optimization of a
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to design, evaluate and implement innovative health and wellbeing interventions. The partnership offers a dynamic and support research environment, with opportunities to collaborate with leading academics
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-motivated research assistant to join our multidisciplinary team to work on the development of novel nanocatalysts and in situ investigation of the structure-property relationship. The successful candidate
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Number: 31395 Posting Number: S06906P Job Description: Provide assistance in various research activities in Dr. Francesca Filbey's Neuroimaging of Reward Dynamics Laboratory located at UT Dallas' Center
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to design, evaluate and implement innovative health and wellbeing interventions. The partnership offers a dynamic and support research environment, with opportunities to collaborate with leading academics
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communication. The person should have a PhD/Master/Degree in social sciences/data analytics and have an appreciation of the cultural dynamics in Singapore and the region. He/she needs to be comfortable with
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Midlands Graduate School Doctoral Training Partnership | Loughborough, England | United Kingdom | 2 months ago
of Nottingham to commence in October 2026. Project overview This project investigates how housing inequalities spatially structure wellbeing in cities. It begins from the premise that where we live — and the
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to domain-specific knowledge and research. All three domains – life & medical sciences, earth sciences, and energy systems/materials – are characterized by the generation of huge heterogeneously structured