Applications are now closed
The Channel 4 Scholarship Programme runs for five years, giving graduate students hands on experience in their chosen business area. The graduates will attend University College London on a part time basis working towards a PHD. Coaching will be provided by a member of the HR team.
AT&I (Audience Technology and Insight)
AT&I are actively looking to build a team of technical analysts to deeply mine the data we will collect from our viewers. The media industry is going through a transition with a marked shift from relational databases and backward looking analytics to big data platforms with real time and predictive analytics.
We are looking to invest in upcoming talent and graduates that have the raw skills and technical training, but perhaps lack the practical experience in the industry.
UCL Mphil/PhD entry requirements
1st class or high upper 2nd class BSc degree, or an MSc with merit or distinction in mathematics, statistics, computer science, or a related quantitative discipline.
UCL - Mphil/PhD in Statistics
The UCL MPhil/PhD programme in Statistics aims to develop research students who can eventually make original contributions to the subject. Students are initially registered for the MPhil degree. No sooner than one year, they are transferred to the PhD degree with retrospective effect if they show a capacity for original work.
Research in Statistical Science is based on a blend of project-based research groups, multidisciplinary collaborations and individual research programmes:
This theme is concerned with advancing the theory, methodology, algorithmic development and application of simulation based approaches, such as Markov Chain Monte Carlo, to statistical inference.
Multivariate and High Dimensional Data
This theme has a research programme that encompasses both the theoretical and methodological problems encountered when analysing multivariate and high dimensional data. Much of the work in the area is driven by advances in technology in various application fields, where new forms of data with unprecedented levels of heterogeneity and complexity are in a modern setting collected routinely.
Current application problems that the group works on include medical imaging and near-infrared spectroscopy.
Stochastic Modelling and Time Series
The research carried out under this theme covers the development of generic stochastic models and the investigation of their properties, as well as modelling and inference for applications in a range of physical and biological sciences.
Major components include:
- Modelling and inference for spatial-temporal processes, with important applications in environmental sciences including hydrology, climatology, and atmospheric science
- Theoretical research on epidemic models and genetics, leading to applications in the life sciences and insight on biological mechanisms.
This theme has a research programme that encompasses both applied health research and the development and evaluation of statistical methods. Current methodological topics include risk modelling of health outcomes, modelling clustered data, analysis of health economic data, meta-analysis, missing data, evidence synthesis and Bayesian methods.
Much of the applied research is carried in collaboration with health researchers within the UCLH/UCL Comprehensive Biomedical Research Centre (CBRC) and the PRIMENT CTU. The NIHR grant for the CBRC has enabled the formation of a Biostatistics Group which sits across the UCL Statistics Department and the UCL faculty of Life and Biomedical Sciences. Applied research projects include developing the first risk model for heart valve surgery, developing a severity scoring system for multiple sclerosis, validating risk models for cardiac surgery, measuring variation in general practice outcomes, studying cost effectiveness of decisions on treatments for angina pectoris, and randomised trials in health services research and drug development.
General Theory and Methodology
The research carried out under this theme covers foundational and theoretical aspects of probability and inferential statistics, and generic statistical methodology.
Current research interests include:
- Philosophical foundations of probability and statistics
- Theory of inference, including Bayesian theory, predictive inference and asymptotic theory
- Core Bayesian methodology
- Statistical methodology for causal inference
- Inference for stochastic models, nonparametric and semi parametric inference
- Methodology for multivariate data, including cluster analysis, multivariate calibration and classification
- Machine learning, classification, pattern recognition
- Decision analysis via operational research and financial methods
- Five year fixed term contract with Channel 4 paying £30,000 per year
- UCL - MPhil/PhD in Statistics
- Additional training as required