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portfolio across multiple sectors and disciplines, serve as a key member of the ACEP leadership team, contribute to strategy, operations, and collaboration across programs, lead research teams, build new
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in scientific methodologies that have transformed the study of, and interest for bioarchaeological remains, makes the PhD project highly relevant across multiple academic domains. Although the botany
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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environments—such as fleets with multiple aircraft types. Objectives Objective 1: Map current data types, structures, and interoperability challenges to build a detailed "as-is" understanding of current
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machine learning techniques to predict market behavior and generate alphas Execution. Create strategies to execute on modelling ideas under simulated competition Evaluation. Backtest ideas using historical
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machine learning techniques to predict market behavior and generate alphas Execution. Create strategies to execute on modelling ideas under simulated competition Evaluation. Backtest ideas using historical
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previous experience of successful partnership working with multiple stakeholders, alongside academic research experience, is essential. Details of funding The successful applicant will: Be awarded an annual
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, statistical analysis, and machine learning techniques to predict market behavior and generate alphas Execution. Create strategies to execute on modelling ideas under simulated competition Evaluation. Backtest
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, statistical analysis, and machine learning techniques to predict market behavior and generate alphas Execution. Create strategies to execute on modelling ideas under simulated competition Evaluation. Backtest
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the detection of real versus AI videos. The focus has been from single disciplines (e.g., Masood et al., 2022), and typically technical in nature. By drawing on multiple modalities within video (i.e., visual