658 postdoc-in-thermal-network-of-the-physical-building Fellowship positions in United Kingdom
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talent from across engineering and physical sciences. Research Areas: Any research area within EPSRC's remit across engineering and physical sciences Interdisciplinary approaches that enhance our research
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Physical Sciences , Chemistry Job Type Academic Posts , Research Fellowships , Research Related , Other Research Related Contract Type Fixed Term Hours Full Time Apply on website Save jobClick to add the job
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This is an exciting opportunity for an experienced, highly motivated individual to join our vibrant, multidisciplinary rare disease research team. This postdoc will work within a multidisciplinary
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, meetings and conferences To build and create networks both internally and externally to the university, to influence decisions, explore future research requirements, and share research ideas for the benefit
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Senior Researcher to support the delivery of a range of funded applied health research projects, providing qualitative and mixed methods process evaluations. This is an exciting opportunity for someone who
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applications; To build relationships with both internal and external contacts in order to exchange information, to form relationships for future collaborations and identify potential sources of funds and/or
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analysing the outputs of hydrodynamical simulations of clusters of galaxies to trace the build-up of mass through the cosmic network as clusters grow by mergers or smooth accretion of matter along filaments
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Duties The responsibilities may include some but not all of the responsibilities outlined below. Implement and test different Artificial Neural Network (ANN) architectures, such as convolutional and
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to contribute to an exciting European project developing hydrothermal processes for the management of solid digestate and other waste from the olive oil production process. About the Role We are seeking a
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systems, with emphasis on criteria for robustness, reliability, and stability. Topics of interest include the study of symmetries and equivariance and their implementation in deep neural networks