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Field
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all, the traditional statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental
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Evaluating the role of Big Data and satellite technologies in understanding livestock impacts on the upland landscape DoS: Dr Mark Whiteside 2nd Supervisor: Dr Katherine Herborn 3rd Supervisor: Dr
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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statistical methods are not suitable for big data due to their certain characteristics: heterogeneity, statistical biases, noise accumulations, spurious correlation, and incidental endogeneity. Therefore, big
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-on experiments & development and opportunities for travel to international facilities. This project is supported by the large investment of a URKI Future Leaders Fellowship to identify, synthesise and explore new
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local extinction of large-bodied frugivorous birds and mammals, leaving structurally intact yet defaunated forests missing key ecological functions like seed dispersal for large-seeded plants. Studying
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mismatch remains a key issue for speech and language technologies. Especially for speech technology the variability of input data is large and recordings can occur in highly complex acoustic and linguistic
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health datasets. Ageing is usually quantified as a measurement of the time elapsed since birth. This cannot explain the large variations in ageing trajectories between older people of similar age
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scattering, and rheometry will be conducted to understand the dynamics and interactions between ingredients in the liquid formulation. This information will be correlated with atomic force and electron
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, manipulate large datasets, visualise data and perform numerical and statistical analysis is a requirement. Experience in handling 'big data', machine learning and working in distributed teams, is useful