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Published Thursday 10 Jul 2025 Deadline Monday 15 Sep 2025 Work area PhD Organisational unit Erasmus School of History, Culture and Communication (ESHCC) Salary € 2.901 - € 3..707 Employment 1 fte
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care systems. About the role We are seeking an enthusiastic Research Assistant with a background in social science, participatory action research and creative methodologies, and an interest in social
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exceptional researchers to join our dynamic team. As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis, natural
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. This research will use distributed field data collection (macroinvertebrates, sediment character and dynamics) and a complementary set of flume experiments to quantify these impacts and to systematically
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. The successful candidate will work on field-based experiments, data collection, and analysis, focusing on understanding the interaction between floral resources, pollinator activity, and apple yield outcomes
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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third-cycle courses. The last day to apply is May 30, 2025. Project description and tasks: The PhD student will carry out research in the analysis of Partial Differential Equations as part of a project
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assess global urban transport policy implementations and integrate these insights into the context of Birmingham, identifying policy opportunities to foster behavioural change in use of transport modes
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | about 1 month ago
performance. Throughout this PhD, the successful applicant will gain expertise in cutting-edge modelling approaches and experimental techniques including: Thermogravimetric Analysis (TGA) with Mass Spectrometry
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Simulations (LES). The analysis will be performed together with teams at the Helmholtz-Zentrum Hereon that focus on ocean turbulence and machine learning as a part of the TRR181 Collaborative Research Centre