Research Associate in Data Science for Construction Productivity (Fixed Term)

A position exists, for a Research Associate in the Department of Engineering, to work on Data Science for Construction Productivity. The researcher's responsibilities will include the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity measurement in construction.

The researcher's responsibilities will include the development and implementation of ML, CV, LLMs, and VLMs to automate data extraction and interpretation for productivity measurement in construction.

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• Hold a PhD in Computer Science, Civil Engineering, Data Science, Information Systems, or a related field.
  
• Strong analytical and critical thinking skills.
  
• Strong programming skills for data-to-dashboard applications using data science, machine learning (ML), computer vision (CV), large language models (LLM) for quantitative data, texts, images, and sensor-based data.
  
• Experience in automated collection of unstructured and structured data in different formats, and translating these into a standard format for analysis, interpretation, and dashboard development.
  
• Experience of working with industry partners is desirable.
  
• Excellent English language proficiency.
  
• Excellent verbal and non-verbal communication skills including the ability to write concise and well-presented text in academic papers and/or industry reports.
  
• Evidence of working collaboratively in multidisciplinary teams and able to liaise and work with a full range of the Laing O'Rourke Centre stakeholders including academics and industry.
  

The Laing O'Rourke Centre supports flexible work arrangements. Core working time at the Centre based in the West Cambridge Civil Engineering offices to build team collaboration is expected.

Salary range: Research Associate GBP 37,694 - GBP 46,049

The funds for this post are available for one year in the first instance.

Fixed-term: The funds for this post are available for 12 months in the first instance.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Please ensure that you upload your Curriculum Vitae (CV), a covering letter detailing how your experience meets the person profile requirements, a copy of your degree(s) certificate(s) along with a full transcript, and research publication list in the Upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please submit your application by midnight on the closing date.

If you have any questions about this vacancy, please contact Dr Brial Sheil or Dr Danny Murguia () for queries of a technical nature related to the role and Jan Wojtecki () for queries related to the application process.

Please quote reference NM48665 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

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