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Research Fellow

University of Huddersfield - Huddersfield Business School

Fixed Term for 3 years, 29.6 hours per week

The Northern Productivity Hub at the University of Huddersfield Business School is looking to appoint a Research Fellow to join an exciting research project ‘Cloud Based Dynamic End-to End Control Tower for Supply Chains, A Decision Support System’ to work on the ‘Dynamic End-to-End Supply Chain Data Platform’ within the project and assist with developing ‘AI Solutions for Supply Chains’. This is a three-year project working under the supervision of Dr Sahar Validi (Huddersfield Business School).

The University of Huddersfield is an award winning, successful, and modern University. Inspirational and innovative research is at the core of our vision. The candidate will be based in the Department of Logistics, Marketing, Hospitality and Analytics within the Business School with a wealth of researchers who contribute to the three research centres in the school. The candidate will also work closely with the School of Computing & Engineering for this project. The School of Computing and Engineering provides a research-supportive environment, securing over £25M in external funding from UKRI and Horizon 2020. Research in the Department of Computer Science covers an international portfolio and is conducted within several research centres. The Department of Computer Science is affiliated to the ATLAS Experiment at CERN and conducts research into modelling and simulation. Our research cuts across disciplines and we welcome interest from candidates with interdisciplinary mindsets to contribute to existing areas of research, open up new avenues of endeavour and support our growing and diverse doctoral research community.

Project Brief

  • Aim: This project intends to build a Cloud-Based Control Tower for Supply Chains (SC). This Control Tower will be designed as a Tailored Intelligent Decision Support System to enable SMEs and other organisations to obtain a wider view and insight into SCs and how to optimise them.
  • Thematic drivers: This interdisciplinary project brings together main areas of Supply Chain management, Operational Research, Computer Science, and Digital Transformation to develop an Intelligent Decision Support System.
  • Key overarching questions:

-      How to design a system to make a shift from reactive to predictive and use a combination of analytical methods and digital technology processes to develop a Supply Chain Control Tower that is capable of learning the behaviour of the entire SC?

-      How to move from general-purpose “black-box” solutions to an AI enabled tailored decision support system for SMEs?

The Research Fellow will be required to:

  • Conduct a comprehensive review of literature across disciplines (Supply Chain Management, Operational Research/Management Science, Decision Support Systems, Data Analytics, Artificial Intelligent Solutions, etc.) undertaking a review of interpretability, explainability, and data imbalance approaches that can be exploited to improve AI-based solutions for SCs
  • Work with the team to deep dive into selected supply chains (SCs), and develop dynamic visualised maps, models & networks of SCs, by sector and at regional, national, and international scales.
  • Work with the team to develop a cloud-based dynamic end-to-end SC data collection/data access platform, and test models in the planned Technology and Operational Research Living Lab and develop bespoke AI-based solutions for particular case studies.
  • Building on the findings of the modelling phase, work with the team to develop tailored solutions for SMEs.
  • Based on the accumulated knowledge, work with the team to fine tune the tested control tower.

For further details about this post (including preparatory reading material) and to make an application please visit or contact

For further details about this post and to make application please visit:

Closing date: 24 January 2022

Interview date: 23 February 2022

Working for Equal Opportunities.

Innovative University. Inspiring Employer


Location: Huddersfield
Salary: £28,523 to £32,084
Hours: Part Time
Contract Type: Fixed-Term/Contract
Placed On: 12th January 2022
Closes: 24th January 2022
Job Ref: R6238
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