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KTP Associate

School of Digital, Technologies and Arts

Location:  Stoke Campus
Salary:   £24,871 to £28,756 Per Annum
Tenure:  Full time Fixed Term for 24 months
Release Date:  Tuesday 26 April 2022
Closing Date:   Tuesday 24 May 2022
Interview Date:   To be confirmed
Reference:  DTA21-14

Who is Staffordshire University?  

 We are the Connected University with 100 years of experience and ambition in becoming the UK’s foremost digital Institution. Our main campus is located in Stoke on Trent alongside our Centres of Excellence in Healthcare Education located in Stafford and Shrewsbury. Staffordshire University London’s Digital Institute is our first campus outside the Midlands. 

With more than 10,000 Full Time Undergraduate and Postgraduate students on campus, we continue to drive innovation and change, aiming to positively disrupt our sector. For our University, it is about so much more than the numbers. In fact, if there’s one thing that sets us apart, it’s our people who are all #ProudToBeStaffs. Every one of our employees goes above and beyond to deliver on our connected mission, responding to the needs of our students, academic partners, businesses and society.  

Over the past 5 years, we have transformed ourselves into a Gold standard provider of teaching and learning, gaining historically high positions in the UK league tables. With digital skills being at our core, we strive for diversity in all its forms and play an important role in our local communities and regional economies. 

About the role  

Connexica and Staffordshire University KTP – Developing an AI and Machine Learning Dashboard for SMEs. 

We are seeking a highly committed, motivated and enthusiastic person to join our team on a Knowledge Transfer Partnership (KTP) funded project.  

AI and Machine Learning-based analytics has become the most talked about aspect of the analytics industry over the course of the last five years, with the potential to supply next-generational insights based on complex data models and providing organisations with a reliable evidence base for their decision making. Access to these tools deliver significant business benefits to organisations by offering new ways of dealing with long-standing challenges and providing a platform which facilitates innovation. 

However, for most organisations due to the complexity and associated costs of this technology the benefits that it has the potential to deliver remain out of reach. Few SME's have the specialist data science expertise to create data models and interpret the result sets that they generate, or the budgets to invest in high-end technology tools to assist with this process. 

This project aims to remove the current cost and complexity barriers that SME organisations typically face in accessing the benefits that AI-based analytics can deliver by developing cutting-edge data modelling concepts and new innovative ways to make them accessible and useful to non-specialist users. 

The project requires the creation of new knowledge to enable the development of explainable AI solutions. The knowledge transfer required is largely the Explainable Artificial Intelligence (XAI) and machine learning techniques to enable Connexica to make powerful Machine Learning (ML) models accessible and interpretable.  

This KTP associate will develop algorithms for a simple explanation of the decisions of black-box models to non-specialists. This will be a key aspect of the knowledge transfer.

The Associate will have Bachelor's degree, 2.1 or 1st and preferably a postgraduate degree in Computer Science. This should give them a sound knowledge of multiple programming languages with emphasis on python and java engine as these are the requirements for the development of new Machine Learning platforms.  

It is desirable for the Associate to have experience developing machine learning techniques especially if this involved XAI knowledge and understanding. An understanding of how to train, test and validate deep learning models is desirable in order to develop intelligent AI and systems for Finance, Healthcare, and Retail scenarios. It is desirable that they have gained at least 2 years of commercial experience in a similar or relevant industry to demonstrate their experience on similar projects, ideally from inception to delivery.  

The Associate will be a team player so as to allow them to integrate with Connexica programmers and designers. They should be dependable and have good interpersonal skills and be effective communicators. The Associate should be skilled in planning and able to meet agreed deadlines.

Should you require a informal discussion about the role, please contact Mr Alex Hurley and Dr Mohamed Sedky

This role is located across both our Stoke Campus and Connexica Ltd in Stafford.

This post is for a 24-month fixed term contract.

In return for your dedication, we have a competitive benefits package available

 Competitive incremental rates of Pay

  • 32 days Annual Leave plus 11 days Bank Holiday and Discretionary days
  • Excellent Pension Scheme
  • Access to continued professional and personal development
  • An opportunity to become part of the wider University community
  • Access to an Employee Assistance Programme
  • Discounted Health & Fitness Facilities on site at the Stoke Campus
  • Discounted Travel by Rail or Bus, with the option of season tickets loans 

We reserve the right to close any vacancies when we are in receipt of sufficient applications. All applicants are advised to complete and submit your applications as soon as possible.  

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Further details:

Staffordshire University is committed to promoting and enabling a positive culture where staff, students and visitors are confident to be their authentic selves. We focus on inclusion as a way to ensure equality of opportunity for all our people and to demonstrate our commitment to Equality, Diversity and Human Rights.

We promote applications from all sections of the community, regardless of background, belief or identity, recognising the benefits a diverse organisation can bring for the University. 

We particularly encourage applications from Black, Asian and Minority Ethnic (BAME) people, who are currently under-represented in the University workforce.



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