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of original machine-learning based algorithms and models for multi-modal ultrasound guidance that are intuitive for a non-specialist to use while scanning and trustworthy. You will work with clinical domain
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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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Bay. The key responsibilities of this role include; Using a combination of automated algorithms and manual data processing to identify bottlenose dolphin signature whistles in a multi-year acoustic
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candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development for various hydrogen technologies-based energy systems. Responsibilities
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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
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. You will focus on developing microwave techniques and associated electronics to precisely control the curing process, using AI-based algorithms to optimise outcomes. Full support will be provided
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inversion techniques and signal processing. Strong programming skills, Proficiency in scientific computing (e.g. Python, MATLAB, or similar) for algorithm development and data handling. Experience with sensor
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algorithms that work in-the-loop, and deliver empirical work and publications. Main Duties and Responsibilities 1. Take a leading role in the planning and conduct of assigned research individually or jointly
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. - Collaborating with interdisciplinary teams to design and implement innovative solutions in MLOps. - Developing and optimizing algorithms for model compression and efficiency improvement. - Staying abreast
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits