Study location	United Kingdom, Newcastle City Campus
Type	Master courses, full-time
Nominal duration	1 year
Study language	English
Awards	MSc

Entry qualification	Undergraduate diploma (or higher) 2.2 classification construction-related undergraduate degree or an equivalent professional qualification with professional practice experience in a subject area

Language requirements	English Accepted proof of proficiency: Cambridge English, IELTS, TOEFL or other equivalent IELTS: 6.5 (with a minimum of 5.5 in each band)

Other requirements	At least 2 reference(s) must be provided.

More information	northumbria.ac.uk/..ith-bim-msc-ft-dtfcpj6

Overview

Interested? To learn more about this study programme, entry requirements and application process, please contact one of our consultants in a country nearest to you.

Career opportunities

This course will open up opportunities in management roles in construction-related organisations, particularly internationally-driven contracting companies. Past graduates have gone on to work for companies such as Arup, Arcadis, BAM Construct UK, BDP, Bouygues Construction, Carillion, Kier Group, Laing O’Rourke, Mace, Mott MacDonald, Ryder Architecture, Sir Robert McAlpine, Skanska and Turner & Townsend. Job roles have included BIM coordinators, design managers, digital engineers, directors, management consultants, project managers and technical specialists.

The course could also lead you to a postgraduate research degree such as an MPhil, PhD or Professional Doctorate. If you decide to start up your own business, it’s good to know that the combined turnover of our graduates’ start-up companies is higher than that of any other UK university.

Whatever you decide to do, you will have the transferable skills that employers expect from a Masters graduate from Northumbria University. These include the ability to tackle complex issues through conceptualisation and undertaking research, the ability to contribute to new processes and knowledge, and the ability to formulate balanced judgements when considering incomplete or ambiguous data.