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opportunities. Be mentored by internationally recognised research leaders Our cohort-based, 4-year scheme offers a distinctive PhD training experience. During this structured PhD programme, you will complete
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three of the following areas: Python programming Develop LLM-based tools to automate data connector generation for data ingestion. Design and implement a multi-layered storage strategy for scalable PBM
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relevant Master's degree (or exceptional Bachelor's) in biomedical/mechanical engineering, materials science, or computer science, with experience in mechanical design/textiles and programming (Python/MATLAB
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strong teamwork and communication skills, reliability, attention to detail, effective time management, and the ability to independently lead their own programme of research. You will have an MSc and
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), or international equivalent, in Engineering, Computer Science, Physics or Mathematics with evidence of programming experience. Equality, diversity and inclusion is fundamental to the success of RAINZ CDT and is at
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), or international equivalent, in Engineering, Computer Science, Physics or Mathematics with evidence of programming experience. Equality, diversity and inclusion is fundamental to the success of RAINZ CDT and is at
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have a 1st or high 2:1 degree in electrical/mechanical engineering, physics, mathematics, or related disciplines. Skills in numerical tools and programming are desirable. Any experience in engineering
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and travel Requirements The candidate should have a 1st or high 2:1 degree in electrical/mechanical engineering, physics, mathematics, or related disciplines. Skills in numerical tools and programming
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, training, and collaboration Preferably a strong background in aircraft design and propulsion systems Preferably Proficient in programming (MATLAB preferred; Python is also acceptable) Prior experience with
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advantageous. Familiarity with space-grade hardware and radiation effects on electronics is beneficial but not essential. Strong programming skills in Python, C/C++, or HDL, along with analytical problem-solving