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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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Specification Hold or be close to obtaining PhD in theoretical physics or related area High level analytical capability Ability to communicate complex information clearly Fluency in relevant models, techniques
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to the creation of knowledge by undertaking a specified range of activities within an established research programme and/or specific research project. We are looking for up to two Postdoctoral Researchers
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Intervention Responsive Studies Team (PHIRST) Fusion, funded by the National Institute for Health Research (NIHR), Public Health Research (PHR) Programme. You will perform the role of Knowledge Exchange Broker
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analytical capability Ability to communicate complex information clearly Fluency in relevant models, techniques or methods and ability to contribute to developing new ones. Fundamental knowledge concerning
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interdisciplinary project you will also build a stage to allow subsequent characterisation of these MDa. complexes via microscopy. You will develop standard operating procedures for the instrument using, large
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time management and problem-solving skills. Ability to design, modify and operate experimental and pilot equipment; to make and interpret observations reliably. Ability to communicate complex information
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quantitative data analysis: applied machine learning, statistical analysis, and handling complex data. Programming skills in Python and R are essential Experience in applying computational methods to research
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of complex parts, with increased productivity and quality. The proposed research is an exciting merger of leading UK research units, highly innovative small to medium enterprises, and multinational
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project, with demonstrable experience and sufficient specialist knowledge in public health, planning and/or environment-related policy and decision making to contribute to the Groundswell programme