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work alongside renowned academics and researchers in ENU’s School of Computing, Engineering and the Built Environment. If you are someone with expertise in multimodal speech processing and AI algorithms
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and algorithm or approaches, and instead will have a creative approach to problem solving, exploring multiple potential techniques. Ideas will be verified on software systems (e.g. SOLIDWORKS, MATLAB
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. The scope of the research will encompass aspects such as network monitoring, routing algorithms and network-hardware benchmarking. About you You should possess a MSc/MEng in Engineering, Computer
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subject area or subject specialism A4 Conversant in Python programming and deep learning algorithms for image analysis. For appointment at Grade 7: A5 Normally Scottish Credit and Qualification Framework level
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bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms Downloading a copy of our Job Description Full
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project aims to address the current limitations of traditional frame-based sensors and associated processing pipelines with a new family of algorithmic architectures that mimic more closely the behaviours
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algorithms and models, and scientific computing programming (e.g. in MATLAB), and (5) modelling of material degradation and wear-out, reliability prediction models. Familiarity with failure modes of electronic
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to numerical simulation algorithms? Then apply now to join our team of theoretical researchers in the Quantum Information and Quantum Many-Body Physics research group. Your personal sphere of play: As a
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for AI based algorithms. Research experience in these areas will be highly valued. The successful candidate will also contribute to the formulation and submission of research publications, development
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Responsibilities Develop suitable algorithmic methods for live and real-time analysis of synchronous and asynchronous data. Write research reports and publications. Analyse and interpret the results of own research