Research Assistant/Associate in Digital Twinning for Buildings and Districts

 

Salary:

Research Assistant: £32,546 to £34,132  per annum

Research Associate £35,116 to £37,174 per annum

 

Newcastle University is a great place to work, with excellent benefits. We have a generous holiday package; plus the opportunity to buy more, great pension schemes and a number of health and wellbeing initiatives to support you.

 

Closing Date: 27 March 2025

 

 

The Role

We are seeking a highly motivated and skilled Research Assistant / Associate to contribute to our research efforts in the development and application of digital twin technologies for buildings and city districts. 

 

You will play a key role in the development and implementation of digital twins in the built environment using novel approaches for efficient and sustainable data use. In particular, you will contribute to the development and demonstration of building and urban digital twins through federated and distributed data management approaches such as dataspaces. 

 

You will be part of an EC Horizon Europe co-funded project (WILSON: https://wilson-project.eu/) working with leading partners from across the EU on developing effective and efficient approaches for dealing with decentralised heterogeneous environments for data sharing and reuse across various domains. You will also contribute to the development of a predictive maintenance tool to train asset degradation models using asset data from a building portfolio.

 

You will also play a key role in helping the project team test the research outcomes in the WILSON living lab and large-scale pilots, including the local Newcastle Helix (https://www.ncl.ac.uk/who-we-are/helix/). 

 

Working under the WILSON project, you will have the unique opportunity to participate in a multidisciplinary environment, collaborating closely with 15 partners including Universities, SMEs and industry, from across 10 European countries. You will work alongside another Wilson Research Associate and be part of the Newcastle University’s Digital Innovation in Construction & Engineering Lab (NU-DICE Lab: https://research.ncl.ac.uk/kassem/). 

 

This full time position (37 hours per week) is available immediately on a fixed term basis for up to 32 months.

To apply, please complete an online application and upload a plain text copy of your CV and covering letter only. In your covering letter, you should evidence how you meet or exceed the essential and desirable requirements for the role. Please note, any other ‘Additional Document’ you upload may not be received by the reviewing panel.

For more information or informal enquiries, please contact Prof Mohamad Kassem (Mohamad.kassem@newcastle.ac.uk) or Dr Xiang Xie (Xiang.xie@newcastle.ac.uk). 

For further details on the Faculty of Science, Agriculture & Engineering please visit our web page at: here 

 

The Person

 

Knowledge, Skills, and Experience 

•    Digital Twin Data Modelling skills: Proficiency in creating and maintaining federated data models for built environment, including knowledge of Linked Building Data (LBD) ontologies for modelling assets, systems, buildings, portfolios and cities
•    Data management and database skills: Strong experience with database management systems (DBMS), including SQL and NoSQL, for efficient storage and management of complex/large datasets related to buildings and urban environments, particularly live IoT data streams
•    AI and Machine Learning skills: Proficiency in machine learning algorithms, including but not limited to transfer learning, analysing building asset performance. Strong programming skills in Python (or similar) for data analysis and machine learning applications
•    Building Operations & Asset Management Knowledge 

•    Understanding of building operations, including facility and asset management, with a focus on optimising building performance and supporting infrastructure (e.g., EV charging stations)

•    Publications: Demonstrable evidence of prior high-calibre work published, and conference presentations delivered in the field of digital twins and AI applications in the built environment

Desirable

•    Experience with Data Mesh Architecture: Familiarity with data mesh architecture to support data autonomy and openness of both geometric and non-geometric data within the context of a district digital twin
•    Building Automation & Asset Management Systems: Experience working with building automation technologies (e.g., Building Management Systems, IoT sensors) and asset management systems
•    Advanced Data Analytics for Predictive Maintenance: Expertise in analysing complex datasets to derive actionable insights that support predictive maintenance and asset management decision-making
•    BIM/CAD software: Experience with tools for building and urban modelling such as Autodesk Revit, Blender/BlenderBIM, Rhino, SketchUp, or similar BIM/CAD tools
•    Cloud computing: Familiarity with cloud computing platforms (AWS, Azure, etc.) for real-time data integration and analysis
•    Dashboard Development & Data Visualisation: Experience in designing and implementing real-time monitoring dashboards for IoT sensor data, asset performance, building energy usage, etc. Proficiency with Grafana or similar tools for developing interactive, insightful visualisations. Ability to integrate dashboards with various data sources to support decision-making in digital twin environments
•    Prior experience and involvement in EU Horizon, UKRI or related projects is highly desirable

 

Attributes and Behaviour 
•    The ability to work autonomously and the confidence to lead
•    The ability to work independently and collaboratively with colleagues and external industry partners
•    Personal motivation and drive
•    Excellent organisational and planning skills
•    Thrives in a project environment with the ability to work to tight deadlines
•    Strong interpersonal skills with the ability to communicate at all levels to different stakeholder groups in both academia and industry 
•    Excellent verbal, written and presentation skills

 

Qualifications
•    MSc (Research Assistant level) in Computer Science, Data Science, Civil Engineering, Architectural Engineering, or related fields
•    PhD (Research Associate level) in same disciplines as above
 

 

Newcastle University is a global University where everyone is treated with dignity and respect.  As a University of Sanctuary, we aim to provide a welcoming place of safety for all, offering opportunities to people fleeing violence and persecution.

 

We are committed to being a fully inclusive university which actively recruits, supports and retains colleagues from all sectors of society.  We value diversity as well as celebrate, support and thrive on the contributions of all of our employees and the communities they represent.  We are proud to be an equal opportunities employer and encourage applications from individuals who can complement our existing teams, we believe that success is built on having teams whose backgrounds and experiences reflect the diversity of our university and student population.

 

At Newcastle University we hold a silver  Athena Swan award in recognition of our good employment practices for the advancement of gender equality.  We also hold a Race Equality Charter Bronze award in recognition of our work towards tackling race inequality in higher education REC.  We are a Disability Confident employer and will offer an interview to disabled applicants who meet the essential criteria for the role as part of the offer and interview scheme.

 

In addition, we are a member of the Euraxess initiative supporting researchers in Europe. 

Requisition ID: 27921