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Fully Funded PhD Studentship (UK Students Only) Real-Time Sub-THz Electromagnetic Sensing and Machine Learning for Dynamic Particulate Characterization University of Birmingham with support from
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15th October 2026 Languages English English English The Department of Information Security and Communication Technology has a vacancy for a PhD Candidate in Cyber Risk Management in Maritime
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applicants with a background or experience in: • Computational chemistry • Materials simulation • Scientific machine learning / AI • Molecular dynamics or DFT • Materials science or a related discipline
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technology be designed and evaluated so that it is usable, acceptable and aligned with users’ communication preferences and everyday lives? Your role Your PhD will primarily focus on computer vision and
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machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a biological reference point for identifying disease-specific biomarkers. A central part of the
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, ultimately, predictable by machine learning. Specifically, you will build a first-in-class framework to expedite the design of high-affinity binders that engage with therapeutic targets or efficient (bio
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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prepared for changes to your work duties after employment. Required selection criteria You must meet the requirements for admission to the Doctoral Programme in Computer Scienc e, see Section 6-1 of the PhD
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selection criteria Knowledge of sensors and measurement techniques Experience from the industry providing sails for merchant ships Experience with Computational Fluid Mechanics Knowledge of machine learning
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of tax data. Core goals include creating a semantic repository for storing and indexing tax documents, designing machine learning algorithms to represent data in embedding spaces, and building tools