School of Computing, Engineering & Physical Sciences in partnership with Hart Lifts

Job Title:       Internet-of-Things and Machine Learning/Artificial Intelligence KTP Associate

Req No:         Needs to be the same as before

Location:      Glasgow and occasional travel to Paisley

Salary Scale: £28,500 to £33,500 per annum, plus £4000 personal development budget

Full-time:       37.5 hours per week

Fixed Term:   30 months

An exciting opportunity for a KTP associate in IoT and ML/AI applications has become available to work full time on a 30 month Knowledge Transfer Partnership (KTP). The aim of the project is to improve the conventional maintenance and services practices in vertical transportation sector.

Key duties for the successful KTP Associate will include assessing the existing IoT framework, developing IoT enabled network to monitor the lift performance, stream key performance indicators from on-board sensors and controller using suitable wireless communication protocols and then train and embed IoT and machine learning capabilities within the company.

Hart lifts have over 25 years’ experience at the cutting edge of vertical transport within buildings.

Servicing an extensive portfolio of diverse clients from private single owners to leading property companies and care homes to large commercial and retail developments including Tunnocks, Skypark, Knight Frank and Gleneagles Hotel.

The successful candidate will have the opportunity to register free of charge for a Higher Degree (Masters or Ph.D.), receive training in Chartered Management Institute (level 5), work with senior company management to realise benefits to the business and apply their degree and lead their own project in a business environment.

Find out more by visiting:

About KTP:

This position forms part of the Knowledge Transfer Partnership (KTP) funded by Innovate UK. It’s essential you understand how KTP works with business and the University, and the vital role you will play if you successfully secure a KTP Associate position. Visit: http://www.ktp-uk.org/ or contact Stuart McKay stuart.mckay@uws.ac.uk

The successful candidate must possess:

A minimum of 2:1 in MSc in Computer Science/Data Science or a relevant degree in the areas of Software Engineering/Development, Information Technology, or Telecommunication.

The ideal candidate will have expertise in programming language like Python, Java, C/C++ or Matlab, prior experience of working with machine learning libraries such as Scikit-learn, TensorFlow, Keras, H2o.ai, experience in developing IoT applications and services using Raspberry Pi or Arduino boards. Hands-on experience of setting up long-range IoT sensing networks is essential.  

You should have good project management skills, strong analytical and numerical skills with the ability to plan your work under your own initiative and work to deadlines. Strong skills in documentation, report writing and presenting to a diverse audience will be necessary for this post.   

If you have questions about this vacancy contact: Dr. Zeeshan Pervez zeeshan.pervez@uws.ac.uk or Damian Dolan damian@hartlifts.co.uk

Further information, including details of how to apply is available at http://www.uws.ac.uk/about-uws/jobs

Closing date: December 4, 2019

Interviews to be held: December 17, 2019

UWS is committed to equality and diversity and welcomes applications from underrepresented groups.

UWS is a “Disability Confident” employer.

University of the West of Scotland is a registered Scottish charity, no. SC002520