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Modern cyber-physical systems (CPS), such as UAVs, next-generation fighter aircraft, and command-and-control (C2) platforms, integrate digital computation with physical processes to make mission
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by the Ada Lovelace Centre and the University of Birmingham. This interdisciplinary project is ideal for candidates with a background in physics, materials science, chemistry, or computational science
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to the launch of the Bloomberg Cambridge University Corporate Bond Index later in 2025 and the delivery of the ongoing research programme related to the index project. The successful candidate will undertake desk
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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This PhD project aims to advance Safe and Sustainable by Design (SSbD) pharmaceutical manufacturing by integrating cutting-edge methodologies, including computer-assisted retrosynthesis, end-to-end
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/physics/biology) or engineering. The ideal candidate should have some understanding in the areas of Materials Science, Chemistry, Physics, Metallurgy, or Mechanical Engineering. The candidate should be self
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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had
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candidates with: • Relevant subject matter experience at required level (e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) • Willingness to adapt and work across different
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. The high prevalence of iron deficiency in athletes is likely due to a combination of inadequate iron intake (low energy intakes and vegetarian/vegan diets) and increased iron losses associated with physical
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(e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) Willingness to adapt and work across different disciplines Ability to work independently and cooperatively Commitment