Home

People

Find people

Search or browse profiles of over 200 Big Data researchers at Cambridge.
Research network

Research

Big Data research at Cambridge brings together fundamental research into data analysis methods with applications in science, medicine, technology and society.

Events

Monday, 20 May 2019, 12.00pm to Tuesday, 21 May 2019, 6.30pm

The development of machine learning programming languages is critical to support the research and deployment of ML solutions as data-size and model-complexity grow. These languages often offer built-in support for expressing machine learning models as programs and aim at automating inference, through probabilistic analysis and simulation or back-propagation and differentiation. Machine learning languages enable models to be deployed, critiqued, and improved, support reproducible research, and lower the barrier for the use of these methods.

News

About the studentship

The Alan Turing Institute offers a number of places each year to motivated graduate students to receive full funding to undertake a PhD at the University of Cambridge.  The Turing doctoral studentship scheme combines the strengths and expertise of world-class universities with the Turing’s unique position as the UK’s national institute for data science and artificial intelligence, to offer an exceptional PhD programme.

About us

The Cambridge Big Data Strategic Research Initiative brings together researchers from across the University to address challenges presented by our access to unprecedented volumes of data. Our research spans all six Schools of the University, from the underlying fundamentals in mathematics and computer science, to applications ranging from astronomy and bioinformatics, to medicine, social science and the humanities

In parallel, our research addresses important issues around law, ethics and economics, in order to apply Big Data to solve challenging problems for society.

Cambridge Big Data supports collaboration and knowledge transfer in this growing field. 

Join us.

Follow us on Twitter