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- Tasks: Develop and implement machine learning and computer vision for construction productivity.
- Company: Join a leading university's engineering department focused on innovative research.
- Benefits: Competitive salary, flexible work arrangements, and collaboration with industry partners.
- Why this job: Make a real impact in construction through cutting-edge data science technologies.
- Qualifications: PhD in relevant fields and strong programming skills required.
- Other info: Dynamic team environment with opportunities for professional growth.
The predicted salary is between 37694 - 46049 £ per year.
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.
Responsibilities:
- Development and implementation of ML, CV, LLMs, and VLMs to automate data extraction and interpretation for productivity measurement in construction.
Qualifications:
- 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, ML, CV, and 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 bbs24@cam.ac.uk or Dr Danny Murguia (dem52@cam.ac.uk) for queries of a technical nature related to the role and Jan Wojtecki (centre.manager@construction.cam.ac.uk) 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. The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
Research Associate in Data Science for Construction Productivity (Fixed Term) in Cambridge employer: University of Cambridge Vet School
Contact Detail:
University of Cambridge Vet School Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Associate in Data Science for Construction Productivity (Fixed Term) in Cambridge
✨Network Like a Pro
Get out there and connect with people in the industry! Attend events, join online forums, or even reach out to alumni from your university. Building relationships can open doors to opportunities that aren’t even advertised.
✨Show Off Your Skills
Don’t just tell them what you can do; show them! Create a portfolio showcasing your projects in machine learning, computer vision, or any relevant work. This gives potential employers a tangible sense of your capabilities.
✨Ace the Interview
Prepare for interviews by practising common questions and scenarios related to data science and construction productivity. Be ready to discuss your past experiences and how they relate to the role. Confidence is key!
✨Apply Through Our Website
Make sure to apply through our website for the best chance at landing the job. Follow the application instructions carefully and ensure all your documents are in order. We want to see you succeed!
We think you need these skills to ace Research Associate in Data Science for Construction Productivity (Fixed Term) in Cambridge
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your relevant experience in data science, machine learning, and construction productivity. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain how your background meets the qualifications listed in the job description. We love seeing enthusiasm and a clear connection between your experience and our needs.
Follow Application Instructions: Pay close attention to the application instructions. Make sure you upload all required documents like your CV, cover letter, degree certificates, and research publication list. We can’t consider your application without these, so double-check before hitting submit!
Submit Before the Deadline: Don’t leave it to the last minute! Aim to submit your application well before the midnight deadline. This gives you time to review everything and ensures we receive your application on time. We’re excited to hear from you!
How to prepare for a job interview at University of Cambridge Vet School
✨Know Your Tech Inside Out
Make sure you’re well-versed in machine learning, computer vision, and large language models. Brush up on your programming skills and be ready to discuss specific projects where you've applied these technologies. This will show that you not only understand the theory but can also implement it practically.
✨Showcase Your Collaboration Skills
Since the role involves working with multidisciplinary teams, prepare examples of how you've successfully collaborated in the past. Highlight any experiences with industry partners or academic collaborations, as this will demonstrate your ability to liaise effectively with various stakeholders.
✨Prepare for Technical Questions
Expect technical questions related to data extraction and interpretation. Be ready to explain your approach to automating data collection and how you’ve handled unstructured data. Practising common interview questions in this area can help you articulate your thought process clearly.
✨Craft a Compelling Cover Letter
Your cover letter is your chance to shine! Tailor it to highlight how your experience aligns with the job requirements. Use clear examples from your CV to back up your claims, and don’t forget to mention your passion for construction productivity and data science.
