Research Fellow in Digital twins and Ontologies

Role Description

We welcome applications from talented Digital twins and ontology developers to join our research team to participate on the building innovative ecosystem for UK transport decarbonisation.

About the Role

This work is part of TRANSIT project  TransiT - Digital Twinning for the Decarbonisation of UK Transport.  You will focus on the application of ontology and machine learning to advance the development of smart transportation systems. As a key member of our interdisciplinary team, you will play a critical role in the design, development, and integration of advanced ontologies and machine learning models to support the rapid and radical decarbonisation of transport across all modes including Road, Rail, Air, and Maritime.

Your Key Responsibilities include:

• Ontology Development: Design and develop ontologies to represent complex transportation data and knowledge, ensuring seamless data interoperability across different transport modes and systems.
• Machine Learning Application: Apply advanced machine learning techniques to enhance data analysis, predictive modeling, and decision-making processes within the transportation ecosystem.
• Collaborative Research: Work closely with academic, industry, and government partners to understand their requirements and integrate solutions effectively, fostering strong collaborative relationships.
• Digital Twin Integration: Contribute to the creation and integration of Federated Transport Digital Twins (FTDTs) that will culminate in a Federated Transport System of Systems (FTSoS), addressing interoperability, security, and resilience challenges.
• Demonstrator Development: Develop demonstrators to showcase the practical application of ontology and machine learning in real-world transportation scenarios, providing tangible benefits to stakeholders.
• Knowledge Dissemination: Publish research findings in leading academic journals, present at international conferences, and contribute to knowledge transfer activities through bi-directional secondments and policy support.

About You

You will be educated to doctoral level (or close to completion) in a relevant subject and have experience of developing ontologies, knowledge graph, and machine learning technologies.  With excellent software design and development skills you will be able to contribute immediately to the project objectives.  Your expertise in effective training methods and knowledge of manufacturing processes will be an advantage. In addition, you will have a developing track record of publishing in high quality journals.

About Us

As a specialist postgraduate university, Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique impact here.

Cranfield Manufacturing and Materials theme has been following the ambitious strategy of developing a roadmap for Sustainable Manufacturing and Materials Sectors for 2050 by applying fundamental science and thought leadership via conceiving and maturing the concepts of Smart, Clean and Green manufacturing solutions agnostically across all sectors and through all tiers of the supply chain. This is to support the national aspiration of Net Zero UK by 2050 We offer world-class and niche post-graduate level research, education, training and consultancy. We are unique in our multi-disciplinary approach by bringing together design, materials’ technology and management expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of the manufacturing research. Our capabilities are unique, with a focus on simulation and modelling, and sustainability. They also include work in composite manufacture, metallic glasses, nano-materials (graphene, carbon nanotubes, coatings and sensors), low energy casting, thermal barrier coatings and Wire Arc Additive Manufacturing (WAAM).

Find out more about our work here.

Our Values and Commitments

Our shared, stated values help to define who we are and underpin everything we do: Ambition; Impact; Respect; and Community. Find out more here. 

We aim to create and maintain a culture in which everyone can work and study together and realise their full potential. We are a Disability Confident Employer and proud members of the Stonewall Diversity Champions Programme. We are committed to actively exploring flexible working options for each role and have been ranked in the Top 30 family friendly employers in the UK by the charity Working Families. Find out more about our key commitments to Equality, Diversity and Inclusion and Flexible Working here.

Working Arrangements

Collaborating and connecting are integral to so much of what we do. Our Working Arrangements Framework provides many staff with the opportunity to flexibly combine on-site and remote working, where job roles allow, balancing the needs of our community of staff, students, clients and partners.

How to apply                                   

For an informal discussion about this opportunity, please contact Dr. Bernadin Namoano, Lecturer in Digital twins and Machine Learning, (E): bernadin.namoano@cranfield.ac.uk

Please do not hesitate to contact us for further details on E: hrrecruitment@cranfield.ac.uk. Please quote reference number 4946.

Closing date for receipt of applications: 5 November 2024

Please note that we reserve the right to close this advert prior to the stated closing date should we receive sufficient numbers of applications. Therefore, we would encourage you to complete and submit your application as soon as possible.