Data Scientist (NLP and Machine learning) - KTP Associate
University of the West of Scotland (UWS) in Partnership with SERIC
SCHOOL OF COMPUTING, ENGINEERING & PHYSICAL SCIENCES
Campus: Company Based
Job Title: Data Scientist (NLP and Machine learning) - KTP Associate
Req No: REQ000
Salary Scale: Up to £40,000 per annum, + £5k personal development budget + opportunity to do a higher degree (Ph.D.) at no cost;
Fixed Term: 30 months, with potential for permanent employment
Gain management experience and training
Work with senior company management to realise benefits to the business
The School of Computing, Engineering & Physical Sciences at UWS is well established and an internationally recognised academic centre.
SERIC are an award-winning cyber security consultancy and growing managed service business located in Glasgow City Centre with a strong moral and social conscience; most recently recognised when SERIC won the Best Customer Experience award in the Scottish Cyber Awards in late 2018. SERIC’S drive to ‘do the right thing’ led to the creation of SmartSTEMs in 2014 from the SERIC’s internal CSR (corporate social responsibility) programme, SmartSTEMs which since 2016 has been a charity in its own right, championing inclusion into STEM careers, working actively across the UK.
Find out more by visiting: https://www.seric.co.uk/about-seric/
UWS and SERIC are offering an exciting opportunity to work as part of the SERIC team You will be the key contributor in a hugely important social safeguarding platform, working with some of the latest technical innovations, from machine learning to artificial intelligence, to develop an automated safeguarding platform to prevent misuse of collaborative platforms (social media within education is the primary focus initially to help protect children online), an application that has massive social and political impact with a worldwide potential.
To be successful in this post you should be a post graduate in Computer Science/Software Engineering/Information Technology or have a relevant degree involving a significant amount of software development.
Given the strategic important of the project, SERIC’s management have indicated their intention to retain the associate post-KTP subject to performance.
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. Please visit: www.ktpws.org.uk
The successful candidate must possess:
As a minimum, educated to post graduate level in Computer Science or a relevant degree that combines aspects of software development. Experience of software development in C/C++, Python or Matlab and familiarity with the following technologies would be an advantage: Natural Language processing, deep learning, Artificial Intelligence, Big Data, APIs (client and server); Cloud infrastructure; GNU/Linux; HTML/CSS; Mathematical modelling; Perl; PHP; Scalable services
Essential skills we require as a minimum:
Organisational skills with the ability to plan under own initiative and to work to deadlines
Good communication and interpersonal skills including report writing
Ability to collaborate with colleagues and sharing expertise
Ideal Personal Attributes:
Genuine interest in computer systems design and development
Enthusiasm to learn and explore new technical opportunities
Strong self-starter work ethic
If you have questions about this vacancy contact:
T: Prof Naeem Ramzan, or Mr Craig Devlin or Mr Stuart Macdonald from Seric
E: email@example.com or Craig.Devlin@Seric.co.uk; Stuart.Macdonald@seric.co.uk
Further information, including details of how to apply is available at http://www.uws.ac.uk/about-uws/jobs
Closing date: 12 noon, 24th May 2019
Interviews: Friday 31st May 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