124 machine-learning-"https:"-"https:"-"https:"-"https:" positions at King's College London
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quality assurance framework as it applies to an analytical laboratory Good computer skills including Microsoft Office packages Strong communication skills – orally and in writing Strong planning
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are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models using multimodal data including neuroimaging
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are caused and how people respond to treatments. We will investigate blood and cerebrospinal fluid from patients and use machine-learning to identify the treatment-relevant immune processes, with an emphasis
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opportunity for an enthusiastic machine learning researcher to push the boundaries of multimodal-AI by developing new models that incorporate data across several modalities, including imaging, text, social and
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, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research
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to develop novel computational methods for data integration and analysis Experience with machine learning approaches for biological data modeling and predictive analytics Good communication skills and
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maintain a positive work environment. 5. Strong computer skills (proficient with MS WORD, Excel and web-based applications). 6. Eye for detail and ability to accurately document findings in written
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, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research
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Health Hub (KHP DHH) training team and provide leadership in the design and delivery of innovative, high-quality learning resources. The role is central to PharosAI’s mission of equipping researchers
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, then apply statistical and machine learning techniques to analyse how network activity changes in response to these perturbations. This involves identifying patterns, dependencies, and emergent