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Imperial College London and Imperial College Healthcare NHS Trust (ICHT). The project aims to transform the clinical use of electroencephalography (EEG) by developing and validating machine learning
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transport calculations and programming. Expertise in quantum transport and using machine learning algorithms for first principle calculations will be distinct advantage. You should be able to work
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research. The successful applicant will possess a relevant PhD or equivalent qualification/experience in a relevant field of study (e.g. mathematics, physics, statistics data science, AI, machine learning
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systems. You will also explore the cutting-edge application of AI and machine learning in channel prediction. As an active member of CWI, you will contribute to our world-class research output by publishing
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focuses on developing cutting-edge statistical/machine learning methods for fitting complex, multi-institutional network models to partially observed hospital infection data. This research will directly
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publications. Have experience analysing AUV, BRUV or other marine video datasets; Demonstrate advanced GIS capability (ArcGIS Pro or QGIS) is essential, as is confidence in applying machine-learning approaches
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-volatile memory that is seen as a potential candidate for the replacement of Flash and SDRAM memory. However, it is their ability to emulate the memory and learning properties of biological synapses and
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related to staff position within a Research Infrastructure? No Offer Description We are seeking to appoint a Postdoctoral Researcher for a three-year position in machine learning emulators of ice-ocean
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demand. Responsibilities Apply machine learning techniques, statistical modelling, and chemometric methods to extract meaningful biological insights from multivariate data and complex GCxGC-TOFMS datasets
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background in AI/NLP or speech technologies, with experience in designing and implementing machine learning models. Proficient in software development, including Python, model integration, and system