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. Develop reusable data pipelines and apply algorithms to derive required variables. Produce reports, dashboards and data visualisations to support local quality improvement. Ensure projects comply with
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, post-docs and interns collaborating across universities to build better algorithms, software tools and benchmarks to assess the safety of AI implementations at the software and hardware level. We
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will be able to teach one of the undergraduate courses related to AI/ML, programming languages, data structures and algorithms, operating systems, network security, visualization, and human-computer
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data and machine learning processing pipelines. It will also focus on developing AI algorithms for semantically enriching data assets with domain knowledge, which feed into building knowledge graphs
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systems. Software developed for science can change in unpredictable ways, with algorithms invented and reinvented, and SSCC is flexible and able to adapt to changing needs. SSCC’s software and computing
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leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis of normative frameworks and aggregation rules, and
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, with experience in algorithm development. Confident coding skills and familiarity with modern coding workflows and best practices. Excellent verbal communication skills and the ability to engage
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with MoniRail Ltd and Durham University. The primary focus will be on designing and implementing deep learning and anomaly detection algorithms to analyse large-scale, real-world sensor data collected
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related to software development and research. Understanding of fundamental data structures and algorithms for designing and implementing efficient software and models. Familiarity with cloud platforms and
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for the technical development of the PRADA tool, an understanding of or experience with AI, digital apps and software algorithms would be desirable, as would an understanding of major depression and its