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will be advantageous. Knowledge of machine learning or reinforcement learning techniques will be advantageous. Proficiency in algorithm development using Python will be advantageous
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large, highly diverse and multi-modal datasets (e.g., images, surveys, statistical and sensor data). Familiarity with geostatistical, GDAL, Python, PostGIS/PostgresSQL, Machine Learning, AI, Internet
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, integrating the outcomes to inform future projected trend analysis. Applying statistical and machine learning to project future data analysis. Managing and analysing large data sets using efficient data
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policy relevance. Coordinate modelling activities across multiple projects and deliver high-quality outputs on time. Integrate new methodologies, including AI and machine-learning approaches
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Electronic Engineering, Control Engineering, Computer Science or a very closely related topic: Strong understanding of power electronics principles Excellent knowledge on data-driven machine learning algorithm
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, integrating the outcomes to inform future projected trend analysis. Applying statistical and machine learning to project future data analysis. Managing and analysing large data sets using efficient data
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processes that use data-driven machine learning. Given the span of the IN-CYPHER programme, we are seeking multiple motivated research fellows. Unique in its scope, we are developing technologies that span
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therapeutic discovery and providing commercial growers sustainable methods to meet increasing global food demand. Responsibilities Apply machine learning techniques, statistical modelling, and chemometric
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of Birmingham is inviting applications for a Research Fellow position focused on Machine Learning for Automated Formal Verification. Machine learning has transformed programming, with code generation rapidly
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language requirement of the UK HEI; Have a background or a proven interest in AI foundations and its application in civil and environmental engineering, including machine learning, sustainable construction, climate