Student Placements

We work with innovative organisations to offer business-relevant challenges for our students to address over a placement of around 12 weeks full time or part time. Students can be based either on-site with the partner business, at the University, or a mix of the two.

Multi-disciplinary approach to Big Data

The Lancaster University Data Science Programme combines interdisciplinary teaching from four world-leading departments. Collaborating businesses will benefit from expertise from the Lancaster University Management School, Lancaster Environment Centre, the Department of Mathematics and Statistics and the School of Computing and Communications through one unique programme.

Each project will be undertaken by an appropriately skilled graduate with a background in advanced statistical modelling, computing or environmental applications. Each graduate will be supported by a named academic.

What expertise is on offer?

  • Investigative and analytical expertise in processing data and in the extraction of meaning from complex datasets
  • Techniques for the storage and processing of diverse datasets
  • Approaches to interpreting and integrating information from heterogeneous data sets using methods such as natural language processing, anomaly detection and computational analytics, statistical forensic approaches
  • Understanding the psychological correlation between the recorded action and the human and/or social behaviour

Project examples

  • Extracting novel information from existing host data sources (e.g. profiling customers from resource utilisation)
  • Creating insight from bringing together diverse data sources (e.g. generating insight from the synthesis of public demographic data with host data)
  • Investigating the improvement of existing data analysis solutions
  • Improving data visualisation and communication
  • Capturing insight from public sources (e.g. scraping Twitter to allow inferences about public perception of companies and products)
  • Improving business decision support through enhanced modelling and inference

What is the Process and Timeframes?

Each partner organisation provides an indication to the University of their wish to participate in the programme by the end of December each year. This indication gives details of the number of placements offered and, in broad terms, their likely topics and objectives.

Students are invited to apply for the offered placement opportunities from January. The students are interviewed and selected by the placement hosts. Students are assigned an academic supervisor and are expected to produce a detailed project specification by May. The placements take place from June until September, with the student generally spending the majority of this time on their host's premises.