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Field
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position will contribute to the research programme of the recently founded "AI Hub in Generative Models", a research consortium funded by EPSRC. The goal of the programme is to do research in the area of
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research and real-world impact, leveraging one of the highest-quality financial datasets in the industry. What You’ll Do Conduct research and develop ML models to enhance trading strategies, with a focus on
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at the very top of our game in research, technology, and economics, they will. And while the highly-publicized wave of high-frequency or “flash” trading based on sheer speed of execution might have reached its
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top of our game in research, technology, and economics, they will. And while the highly-publicized wave of high-frequency or “flash” trading based on sheer speed of execution might have reached its
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Classification Title: Post Doc Associate Classification Minimum Requirements: A Ph.D. in biomedical informatics, computer science or a related field. Working experience with large language models
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• Strong quantitative and programming skills; experience with seismic data analysis or numerical modelling is highly desirable• Excellent written and verbal communication skills• Ability to work
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with a background in cognitive psychology, data science or computer science and a willingness to develop skills in computational models of cognitive processes, statistical methods, and programming (R
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such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements
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capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives, including large-scale
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impact, leveraging one of the highest-quality financial datasets in the industry. What You’ll Do Conduct research and develop ML models to enhance trading strategies, with a focus on deep learning and