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PhD Studentship: Dissecting the Molecular Architecture and Function of LMTK3 as a Therapeutic Target
protein, including the interplay between its domains and its diverse, non-canonical functions, remains elusive. This project will build directly upon Professor Giamas's findings to dissect the molecular
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workload, increase usability and generally make the vehicle a special place to be. The project will treat the experience of tranquillity as a phenomenon that can be measured and influenced. That phenomenon
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Tenants’ Association. The supervisors represent expertise in: Sustainable architectural design, building transformation and renovation (Prof. Paula Femenías, Chalmers) Sociology with focus on environmental
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This fully-funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA), Cranfield University and Spirent Communications, offers a bursary of £25,000 per annum, covering full
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the field of Computational Morphodynamics in plants. The work will be within the ERC-funded project RESYDE (https://resydeproject.org ) with the aim of building a virtual flower using multi-level data and
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are highly desirable. Minimum Requirements • A master's degree in a relevant field, such as architecture, landscape architecture or historic preservation. A professional degree or PhD is preferred. In
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publication-oriented, allowing you to build a strong academic and professional track record in energy-efficient and secure AI hardware innovation. By the end of this PhD, candidates will possess advanced
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the field of Computational Morphodynamics in plants. The work will be within the ERC-funded project RESYDE (https://resydeproject.org ) with the aim of building a virtual flower using multi-level data and
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase
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Organisation Job description Project and job description Our project will make use sensing technologies (hyperspectral cameras, NIR and Raman sensors), and an edge-compute AI pipeline to sort used