Research Assistant/Associate in Urban Knowledge Modelling

We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.

Salary
Research Assistant - £33,951 to £35,608.
Research Associate - £36,636 to £46,049.

The Role
We are excited to launch this new opportunity for a Research Assistant/Associate in Urban Knowledge Modelling to join us in the School of Engineering at Newcastle University. You will join an innovative team focused on pioneering advanced knowledge modelling specifically for urban air quality management and proactive environmental governance.

This position aims to design and implement a continuous, multi-modal evidence cycle that seamlessly integrates qualitative textual knowledge, quantitative pollution simulation, and real-world observational data. You will play a key role in bridging this qualitative-quantitative divide by implementing the Knowledge-Augmented Generation (KAG) framework.

Your primary focus will be on utilising advanced KAG architectures (i.e., OpenSPG) to synthesise vast amounts of unstructured textual evidence alongside real-world observational time-series data from urban sensor networks into a structured, multimodal Urban Air Quality Knowledge Graph. This will involve: investigating how this multi-modal knowledge can be rigorously aligned to mitigate noise and filter spurious correlations; deploying a logical form-guided hybrid reasoning engine within the KAG framework to automate the translation of qualitative policy hypotheses into machine-readable parameters for quantitative simulation models to enable proactive, ex-ante policy testing; and leveraging emerging technologies like Time-Series-to-Text (TS2T) generation and automated causal discovery to process sensor data to create a feedback loop that dynamically updates the KAG relationships based on empirical evidence.

We are looking for candidates who have experience in creating formal ontologies for urban domains, maintaining structured knowledge graphs (e.g., Neo4j), and a strong grasp of advanced AI reasoning frameworks, specifically foundation models, Large Language Models (LLMs), and KAG pipelines. Expertise in integrating computational simulation models, utilising KAG's mutual indexing capabilities, and applying time-series analysis to observational environmental data is highly sought after.

You will join the Digital Innovation in Construction & Engineering Lab (NU-DICE Lab: https://research.ncl.ac.uk/kassem/). The primary mission of the NU-DICE Lab is to drive the digitalisation and digital transformation of the construction and engineering industries, focusing on process efficiency and transformative innovation. The lab's key research themes include digital twins for urban environments, data-centric construction, and decarbonisation through digitalisation.

This full-time position is available immediately on a fixed-term basis for up to 15 months in the first instance. For more information or informal enquiries, please contact Dr Xiang Xie (xiang.xie@newcastle.ac.uk).

To apply, please complete an online application and upload a plain text copy of your CV and covering letter. In your covering letter, please outline how you are meet or exceed all the essential requirements for the role holder as outlined in the job description (available on the university's website, accessed by the 'Apply' button), and highlight any expertise relevant to the position.

As part of our commitment to career development for research colleagues, the University has developed 3 levels of Research Innovation Role Profiles.pdf. These profiles set out firstly the generic competencies and responsibilities expected of role holders at each level and, secondly, the general qualifications and experiences needed for entry at a particular level.

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