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fuels (hydrogen, methanol, ammonia), simulation tools for marine engines and/or fires due to fuel leakages, data analysis methods and their applications for ships, sufficient understanding of appropriate
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validation experiments for modelling • Computational fluid dynamics techniques • Finite element analysis method • Reviewing literature, planning and managing research, writing technical report / paper
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Real-World Impact: Advance cardiology research with cutting-edge AI methods Top-Tier Mentorship: Collaborate with leading experts in AI, visualization, and medicine Compute Power: Access state-of-the-art
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for extracting physiological biomarkers from ECG, PPG, and related sensor data Machine learning and AI for predictive modelling and risk stratification Computational physiology modelling to personalise and
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to the development of multiscale computational models for simulating crack propagation and establishing reliable methods to predict the residual strength of composite structures. The simulations, performed in Ansys
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conferences to disseminate research findings, and mentoring junior team members in preparation for their presentations. In parallel, the principal investigator (PI) will provide mentorship aimed at supporting
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). Experience in interdisciplinary team-based research. Preferred Qualifications: Prior research experience in computational biology, applied mathematics, or quantitative biology. Familiarity with numerical
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Computational verification of high-speed multi-material flows, where physical experimentation is highly limited, is seen as critical by the defence Sector (source: the UK Atomic Weapons
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degreed program 2. Be in good academic standing 3. Be registered full-time for the respective semester (nine semester credit hours during the fall semester, nine semester credit hours during spring semester
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Following NICE Guidance, NHS England (NHSE) has advocated using Coronary Computed Tomographic Angiography (CCTA) as the first line diagnostic test for suspected symptomatic coronary artery disease