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Join our dynamic, multidisciplinary team as a Research Associate and make a transformative impact in scientific machine learning and digital twins for healthcare innovation! This role focuses
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cutting-edge machine learning methods for spatial omics and for multi-modal data integration. The post-holder will also collaborate on the development of new computational methods to support the CoRE’s
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an expert in the use of advanced statistical inference and machine learning methods for the analysis of omics datasets. You will work with a team of data scientists in Manchester and Oxford to create tissue
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and enabling commercial deployment. The work will integrate model based design of experiments, machine learning, hybrid and kinetic modelling (digital twin development), process design, simulation and
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researchers, under the supervision of Prof David Wedge. Collectively, this team has expertise in the analysis of multilevel omic and imaging data; data integration and machine learning; risk prediction. This
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. We plan to use machine-learning to identify markers of listening intentions from data collected via sound recordings, photographs, ecological momentary assessments (EMA), and passively monitored
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The Role Join our growing team to help re-architect and re-implement the University’s research virtual machine (RVM) and high-throughput computing (HTC) platforms. Beyond provisioning and
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students. The computer revolution started here in 1948 when a machine known affectionately as ‘The Baby’, ran its first stored program. The celebrated wartime codebreaker Alan Turing worked on this computer
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The Role Join our growing team to help re-architect and re-implement the University’s research virtual machine (RVM) and high-throughput computing (HTC) platforms. Beyond provisioning and
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are recruiting an enthusiastic and collaborative post-doctoral research associate with expertise in formal methods, machine learning, control theory, numerical analysis, or a related discipline, with a strong