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Responsive Sensing and Analytics team specialises in developing efficient and scalable algorithms designed to equip emergency services with critical safety information and analytical insights. Leveraging
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optimization (e.g. partitioning, distribution, indexing), and join algorithms (e.g. hash vs nested loop) · Experience in CI/CD automation for a data lake using CDK (Cloud Development Kit) or Terraform Preferred
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for business processes in Statistical Interference/Analysis/Modeling, Machine learning and Natural Language Processing, Artificial Intelligence, Algorithms, Data Mining and Modeling, and Big Data Query. Design
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results are aggregated into an overlapping generations (OLG) model for longer-term dynamic forecasting and distributional analysis. Models are frequently updated to reflect the latest economics and
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solutions for distribution power grid with renewable energy sources Development of simulation models and integration of CPS security algorithms into hardware-in-the-loop testbed environment and conduct
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departmental algorithms, the Scheduler critically evaluates the nature and urgency of scheduling requests to provide comprehensive clinical ambulatory scheduling for providers within the department specialty
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security algorithms to be implemented in the next generation of constellation satellites; collaboration with the RF payload colleagues in analysing and profiling the implementation of these algorithms
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other constituencies. Develop and maintain supporting documentation of measurement methods and algorithms, data sources and reporting processes. Conceptualize and develop cross-functional client/unit
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algorithms that run continuously and emit alarms to apps and other tools that could potentially save lives in the event of a large earthquake anywhere across the entire west coast of the U.S. and further as
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derivation of actionable insights. Identify and use suitable technologies, tools and algorithms which can be applied to research/business activities. Work with research group/business area to employ analysis