Research Assistant (Cloud-Based AI)

Research Assistant (Cloud-Based AI)

Part Time – Fixed Term Contract (November 2026 – July 2027) – High Wycombe / Hybrid

Salary £31,861 pro rata

We’re not trying to fit in with the higher education status quo. We’re challenging it. We’re doing things differently – because our students, our staff, and our world need us to.

So this is an exciting moment to join us. We’re boldly reimagining what a university can be: a place rooted in social mobility, a community where difference is celebrated, and an institution that empowers people to become more than they thought possible.

This role will support delivery of Bucks New University funded research project ‘Cloud-Based Smart Digital Twin for Predictive Calibration Management of Weighing Instruments’, by designing, developing and implementing a cloud-based digital twin system that combines mechanical engineering knowledge, AWS cloud architecture and AI/ML techniques to predict and manage the calibration of weighing and measurement instruments.

What we offer:

• a generous holiday entitlement (35 days per annum, plus bank holidays & closure days)
• Hybrid working (dependent on business needs)
• training & development support opportunities
• contributory pension scheme
• free gym membership for our on-site gym
• a range of staff discounts with major retailers.

Please click here to see our wide range of benefits available for employees.
Please click here for our behavioural based interview question bank.
Please click here to view our employee handbook.

If you have the qualities and attributes representative of the University’s values and ambition, we would be delighted to hear from you.  

For further information about this role please contact Estabraq.makiyah@bnu.ac.uk

All applications are to be made in full and online. 

We are committed to promoting an inclusive and diverse workplace and aim to continue building an environment where everyone thrives and can be themselves.

Please let us know if you require any adjustments or support during the recruitment process. We are happy to discuss any reasonable adjustments that would enable you to perform to the best of your abilities in your role. Please reach out to Estabraq.makiyah@bnu.ac.uk if you have any specific needs or if you would like more information on how we can support you

We ensure that our interview/shortlisting Chairs complete the relevant e-learning and/or inclusive recruitment training.

If you’re considering using AI to support your application, we encourage you to question the value it adds. The use of AI tools sometimes erodes authenticity and prevents us from being able to assess the real you. We strongly recommend you prepare your application using your own skills and knowledge and that AI is only used for the purpose of review.

Closing Date: 31/10/2026

Interview Date:   05/11/2026

If you are invited to interview, you will be required to provide evidence of your eligibility to work in the UK, including details of your current immigration status where applicable. Please note that eligibility for visa sponsorship is dependent on the role meeting the relevant requirements, including salary and working hours. Due to the contracted hours and salary associated with this position, we are unable to offer visa sponsorship for this role

BNU is a Disability Confident employer and as such you will be given the opportunity to declare a disability as part of the application process.

Location

High Wycombe

Contract Type

Fixed Term Contract

Salary Range

£30,180 - £33,662

Hours per week

84 hrs in total (Nov 26 - Jun 27)

Closing Date

31/10/2026

Ref No

2140

Job Description

JOB DESCRIPTION

Job Title: Research Assistant (Cloud-Based AI)

College/Professional Service: College of Creative Arts, Technology and Engineering | Grade: E

Location: High Wycombe Campus / Hybrid | Hours: 84 hrs in total from Nov 26 to Jul 27

Responsible to: Project Lead

Responsible for: No line management needed

Job Purpose: To support delivery of the funded research project ‘Cloud-Based Smart Digital Twin for Predictive Calibration Management of Weighing Instruments’, by designing, developing and implementing a cloud-based digital twin system that combines mechanical engineering knowledge, AWS cloud architecture and AI/ML techniques to predict and manage the calibration of weighing and measurement instruments.

Main Duties & Responsibilities of the role:

• Design and implement a complete cloud-based system on Amazon Web Services (AWS) to support the digital twin project, covering architecture, development, deployment and maintenance.
• Apply mechanical engineering principles, including sensor behaviour, material degradation and calibration processes, to inform the design of the digital twin model for weighing and measurement instruments.
• Develop and apply Artificial Intelligence (AI) and Machine Learning (ML) techniques to build predictive capabilities, such as fault prediction, condition-based maintenance and optimisation.
• Write and maintain robust, well-documented code, primarily in Python, to support system development and data analysis.
• Collect and record the data required from weighing scales (e.g. sensor readings, load and calibration data) to support model development, testing and validation of the digital twin.
• Investigate and, where appropriate, implement AWS IoT TwinMaker or similar digital twin platforms to realise the smart digital twin functionality.
• Use MATLAB or similar simulation and modelling tools to validate system performance and calibration predictions, where required.
• Contribute to the testing, validation and continuous improvement of the predictive calibration management system.
• Prepare technical documentation, reports and presentations summarising project progress, methodology and results for the research team and funders.
• Collaborate effectively with academic supervisors, project partners and other researchers to ensure timely delivery of project milestones.
• Comply with relevant legislative and other requirements (e.g., the Data Protection Act 2018 and GDPR; Health and Safety; UKVI; and Equality and Diversity) in all working practices.
• Such other duties temporarily or on a continuing basis, as may reasonably be required.

PERSON SPECIFICATION – Essential Criteria Only

A = Application T = Test I = Interview

Education, Qualifications & Training | Means of Testing

Master's degree in Mechanical Engineering, Computer Science or a related discipline, or equivalent relevant experience. | A

|

Knowledge & Experience |

|

Working knowledge of mechanical engineering principles relevant to weighing and measurement instruments, such as sensor behaviour, material degradation, and calibration processes. | A/I

Demonstrable experience with Amazon Web Services (AWS), including the ability to design and implement a complete cloud-based system from end to end. | A/I

Experience applying Artificial Intelligence (AI) and Machine Learning (ML) techniques to develop predictive systems, for example for optimisation, fault prediction, or condition-based maintenance. | A/I

Skills |

Experience using MATLAB or similar simulation and modelling tools to validate system performance and calibration predictions. | A/I

Strong programming skills, particularly in languages such as Python. | A/T/I

Special Requirements |

Applicants must have the right to work in the UK for a fixed-term contract from November 2026 to July 2027. | A

Behavioural INDICATORS

The BNU Behaviours Framework (BBF) is a framework for all University staff that sets out the key behaviours that exemplify the values and ethos of the University.

Finding solutions Taking a holistic view and working enthusiastically to analyse problems and to develop workable solutions. Identifying opportunities for innovation.

Using resources effectively Identifying and making the most productive use of resources including people, time, information, networks and budgets.

Achieving results Consistently meeting agreed objectives and success criteria. Taking personal responsibility for getting things done.