Applicants must also demonstrate compelling evidence of academic excellence or exceptional research ability. Admission is extremely selective. Suitable undergraduate degrees include Engineering or a related technical subject such as Computer Science, Physics, Chemistry or Mathematics. A mathematically focussed Economics degree can sometimes be suitable preparation. Students will be expected to have strong backgrounds in mathematics and computer programming, as well as practical skills for large-scale experimentation. Applications are welcomed from 'mature' students currently working in industry who have a UK first class honours degree or international equivalent.
A typical candidate for this course is likely to have experience in the following areas:
- Calculus and University-level Mathematics: differentiation, integration, vector calculus, ODEs/PDEs, Fourier series, vector gradients, coordinate systems, etc.
- Linear algebra: vectors, matrices, linear transformations, matrix inversion, eigenvalues and eigenvectors, matrix factorization, SVD, least squares solutions, etc.
- Probability and Statistics: random variables, random processes, expectation, mean and variance, independence and conditional probability, law of large numbers, stationarity, correlation, Markov chains, central limit theorem, etc.
- Inference: maximum likelihood and Bayesian estimation, regression, classification, clustering, Markov models and Hidden Markov models, Monte Carlo, etc.