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skills. Preferred Qualifications: Prior research experience in computational biology, mathematical modeling, or immunology. Familiarity with numerical methods, parameter estimation, and data visualization
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NERC. Person Specification We seek an enthusiastic individual with a degree in geoscience, physical sciences, or computer science. Numerical literacy and experience with coding tools (Matlab or Python
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and optimization of machine learning methods. Candidate’s profile An ideal candidate would typically have: a strong degree or higher qualification in a relevant field (e.g. computer science, mathematics
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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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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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University’s EDI principles Qualifications Research Assistant First degree in engineering or numerate subject (e.g., mathematics, physical sciences, computer science) PhD close to completion in field of Power
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The probabilistic method is a powerful tool which has been especially influential in the fields of combinatorics and computer science. In the context of combinatorics, this method was pioneered by
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, but current methods are not always efficient or optimal. The process lacks an intelligent, informed approach to selecting the best grinding parameters, which can lead to inefficient maintenance actions
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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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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