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Field
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develop models that can read, extract and acquire knowledge from legacy data, coming both in the form of text and in the form of structured data (e.g. physical measurements) to predict characteristics
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understanding of immunology and the central nervous system • Very good written and spoken English • Analytical and creative mindset, with a strong willingness to learn new techniques Desirable experience • FELASA
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or equivalent Skills/Qualifications • Solid knowledge in bioengineering, biotechnology, or biomedical engineering. • Experience or interest in biosensors and biomarker detection. • Fundamentals of analytical
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self-harm rates. You will expand your data wrangling, analytical and programming skills on python and develop expertise in the fields of machine learning, epidemiology, big data analysis, and suicide and
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machine learning for time series, geospatial data or dynamic models; ideally experience with deep learning frameworks (e.g., PyTorch). Strong analytical and conceptual skills for designing and interpreting
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Dalton Building at Manchester Metropolitan University. You will develop skills in computational experimentation, financial data analytics, and systemic risk modelling, with extensive opportunities
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access to preventive care and neighborhood characteristics influence long-term health trajectories. The project applies both econometric and machine learning approaches to identify high-risk groups and to
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PhD studentship in Machine Learning-Based MIMO Radar Sensing for All-Weather Perception in Autonomous Vehicles Award Summary 100% fees covered, and a minimum tax-free annual living allowance
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analytical sciences, e.g. bio-engineering, chemical engineering, biomedical engineering, analytical chemistry. A research-oriented attitude. Ability to work in an interdisciplinary team and interested in
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regulation and access to nature. By integrating Earth observation, spatial AI, machine learning and socio-environmental datasets, the project will reveal where blue networks perform well across UK towns and