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A PhD studentship in RF and Microwave Engineering is available within the Birmingham Emerging Device Technology (EDT) Research Lab, one of the leading interdisciplinary research groups within
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chemistry, physics, materials science, computer science or other related discipline. This 42-month studentship comes with a budget for training, conference attendance as well as for travel between Birmingham
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 14 days ago
: Analyse how curation and drying impact mechanical properties and hygrothermal performance. Develop a Predictive Model: Create a computational model linking operational variables and material properties
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Application deadline: All year round Research theme: Computational Chemistry, Material Science No. of positions: 1 Eligibility: UK students This 3.5-year project is fully funded by industry and home
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, civil, and materials engineering. We welcome applicants with a background in: Computer Science Mechanical Engineering Aerospace Engineering Civil Engineering Physics If you have a keen interest in AI
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for analysing complex materials, structures and model validation. The DIC community has developed guidelines to ensure robust measurements, continually advancing standards through ongoing challenges. In
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research program (I-Break: Wire-based DED Technology Maturation and Landing Gear Application) and other industrial research projects within WAMC. The student will become part of a diverse and dynamic
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Zhongping.Que@brunel.ac.uk for an informal discussion about the project. Eligibility Applicants will have or be expected to receive a minimum 2:1 or 1st class degree in Materials Engineering, or a related
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, Continuum Mechanics, Computer Science, Materials Science, Physics or a related subject, or relevant industrial experience. English language requirements: Applicants must meet the minimum English language
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Title: Predicting and Improving the Quality of Recycled Plastics Using Advanced Metrology and Data Science Research theme: "Materials Characterisation" "Data Science and Machine Learning in