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The Role The role focuses on advancing research in explainable and trustworthy machine learning, with a particular emphasis on mechanistic interpretability and its application to healthcare data
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with cardiovascular or fetal imaging data. • Knowledge of machine learning model development, validation, and clinical translation. • Experience working with DICOM data, PACS systems, and 3D
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the AI system and the user mutually learn from each other. Qualifications To qualify as a postdoctoral scholarship holder, the postdoctoral fellow is required to have completed a doctoral degree or a
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science, or a related field; experience with using and building machine learning models, developing and validating computational analysis workflows, and developing circuit models is preferred; excellent
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well as interpretability of scientific foundation models. The rush to build foundation models has led to the development of large machine learning models in Astrophysics, fluid dynamics, biology, weather prediction, solar
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-physical systems security, protection of critical infrastructure, and adversarial machine learning. The position will involve collaborating with faculty and graduate students on interdisciplinary research
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the groups of Dr Joe Forth, Dr Anthony Bradley, and Project Lead Professor Steve Rannard, applying your expertise in machine learning, cheminformatics, and soft materials to accelerate LAT design and
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Biology is looking for a highly motivated and independent individual to work as a Postdoctoral Associate. Projects in the Bayer lab study how sensory information affects animal behavior at the level of
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asynchronous AI-led chemical optimisation across chemistry laboratories¿. This role sits at the intersection of robotics, machine learning, and chemistry, aiming to develop robotic systems that work
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Classification Title: Postdoctoral Associate Classification Minimum Requirements: The appointee must have received the doctorate in a field appropriate to the assigned duties and responsibilities