Industrial Secondment: AI (Artificial Intelligence) in Infrastructure Engineering

********************Deadline Passed********************

C-DICE is pleased to partner with Imfuna to offer an exciting opportunity for a three-month secondment for postdoctoral researchers. The postdoctoral researcher seconded to this project will gain dedicated mentorship, collaborative interactions, and external collaborations. The secondee will benefit from professional growth, network expansion, real-world impact, and skill augmentation. Successful completion of this secondment can open doors for further collaboration with Imfuna, potentially leading to full-time roles or other advanced research opportunities.

This project will be ideal for a postdoctoral researcher with a background in engineering, computer science, or a related field with a strong emphasis in AI or Machine Learning.

About Imfuna

Imfuna stands as a global leader in the realm of digital infrastructure and property assessment, delivering unparalleled mobile-to-server solutions for custom inspections, documentation, and reporting. Our innovation has graced landmark projects including The Golden Gate Bridge in San Francisco, Three Mills in London, Millennium Tower in San Francisco, and an ancient castle in Scotland. We pride ourselves in our ability to help users solve ineffective and inefficient processes and bring value beyond expectations to replace the mundane with joy. We constantly strive to innovate solutions that address real world problems.

This area of the business is focused on capturing building asset information, managing, and extending the operational life of buildings – directly contributing to more sustainable buildings and infrastructure.

Project Background

Our project zeros in on the intricacies of Reinforced Autoclaved Aerated Concrete (RAAC), particularly addressing the formidable challenges of obtaining precise asset data and making informed evaluations regarding the durability and security of RAAC-embedded structures. Central to this endeavour is Imfuna’s state-of-the-art app, which provides a robust platform for meticulously documenting the prevailing conditions of RAAC in real-world scenarios. But we’re not stopping at mere documentation.

We’re on the precipice of infusing our documentation process with the transformative power of Artificial Intelligence (AI). The objective? To elevate the quality and depth of the captured data, unlocking avenues for nuanced analytics that were previously beyond reach. With AI-driven insights, we can monitor the health of these buildings over extended periods, not just diagnosing potential issues but also prescribing actionable interventions to augment their lifespan.

The implications of this project extend beyond the immediate. By safely prolonging the life of a building, we can significantly curtail both the embedded carbon from construction and the operational carbon during its use. This not only resonates with sustainable building practices but also aligns with global ambitions of a carbon-neutral future.

The mission of this project isn’t restricted to RAAC alone. The insights and methodologies we cultivate here have the potential to ripple across the broader infrastructure ecosystem, setting new paradigms for how we perceive, evaluate, and sustain our built environment.

Job Purpose

Overview:

At Imfuna, we’re poised at the frontier of a transformative project, leveraging the in-depth RAAC research from Loughborough University to craft cutting-edge AI algorithms. These algorithms aim to enhance the safety, sustainability, and longevity of buildings with RAAC structures. Your role as our Postdoctoral Researcher will be pivotal in bridging this academic research with practical AI solutions, having a direct impact on the built environment and the lives of countless inhabitants.

Role and Responsibilities:

Research Translation: Delve into the RAAC-focused data and studies from Loughborough University, distilling complex academic findings into actionable insights. Your expertise will guide the translation of this research into the foundational bedrock of our AI algorithms.

Algorithm Development & Refinement: Craft, train, and refine AI models specifically designed to address the challenges associated with RAAC structures. Your algorithms will leverage research data to predict, assess, and enhance the safety and durability of these buildings.

Integration with Imfuna App: Collaborate with our software development teams to ensure the seamless integration of these AI capabilities into the Imfuna application, enabling users to capture, document, and analyse RAAC conditions with unparalleled precision.

Field Testing & Validation: Engage in rigorous testing of the AI solutions in real-world scenarios. Validate the models against actual RAAC building data, ensuring the results resonate with ground realities and address inherent challenges.

Knowledge Dissemination & Reporting: Maintain comprehensive documentation detailing the development journey, methodologies, and results. Furthermore, collaborate with both our internal teams and Loughborough University researchers, ensuring a symbiotic flow of knowledge and insights, into both industry guidance and academic papers. This role offers more than a job; it’s an opportunity to be at the forefront of a revolutionary endeavour. Your work will not only advance the field of AI in infrastructure but will have tangible, lasting impacts on the safety and well-being of numerous properties and their occupants. Join us in making a profound difference.

Secondment Details

Number of secondments: This advert is for one secondment.

Duration: This secondment is three months in duration at full-time, depending on the secondee’s availability (or prorated for part-time equivalent).

Location: Hybrid working with periodic in-person meetings at Loughborough University or at the secondment host offices in London.

Salary: University Pay Scale Spine 27 to 38 (£33,966 to £46,974 p.a. prorated for duration of post), depending on current postdoctoral researcher salary. Please note that university overheads will not be paid due to the developmental opportunity this presents to the postdoctoral researcher to undertake an industrial secondment. Expenses related to authorised travel for this secondment will be covered.

Special Conditions

This industrial placement is open to postdoctoral researchers based at C-DICE universities. In exceptional cases, final year PhD students (PGRs) will be considered. Successful candidates will be required to seek permission from their supervisor and employing organisation to undertake the secondment. The project will commence as soon as possible. In cases where participation in this secondment would require a no-cost extension to an EPSRC grant, EPSRC has agreed to grant this automatically on request.

All staff have a statutory responsibility to take reasonable care of themselves, others and the environment and to prevent harm by their acts or omissions. All staff are therefore required to adhere to Imfuna Health, Safety and Environmental Policy & Procedures.

All staff should hold a duty and commitment to observing the Imfuna Equality, Diversity, and Inclusion policy and procedures at all times. Duties must be carried out in accordance with relevant Equality & Diversity legislation and policies/procedures.

After the Secondment

• Confirmation of expenditure.
• Outcomes (e.g. publications, engagement activities) for impact tracking.
• A report highlighting key findings.
• The postdoc may be asked to engage with C-DICE events (e.g. Annual Conference or Business Engagement Events) and to lead a C-DICE training activity in their area of expertise.

Eligibility

Essential Criteria

• A Ph.D. in Engineering, Computer Science, or a related field with a strong emphasis on AI or Machine Learning.
• Demonstrated expertise in AI algorithm development, preferably in areas such as deep learning, reinforcement learning, or natural language processing.
• Strong analytical and problem-solving skills, with a keen ability to apply AI techniques to engineering and structural challenges.
• Research and Analysis Skills: Proficiency in conducting research, literature reviews, and analysis of relevant projects. Ability to critically evaluate research findings, identify trends, and extract key metrics.
• Excellent communication skills, including the ability to collaborate effectively with multidisciplinary teams and present research findings.
• Analytical Thinking: Strong analytical skills to assess and evaluate the value, impacts, and potential benefits of digitally enabled data.

Desirable Criteria

• Knowledge of materials or structures: Some understanding or familiarity with building materials) or traditional reinforced concrete would be useful, but not essential.
• A desire to gain an understanding or appreciation of RAAC and the structural properties of building assets. Even if not an expert, a basic understanding or willingness to learn would be useful.
• Software Integration: Understanding of how AI models can be integrated into software applications. Experience with mobile or web app integration would be a plus.
• Bridging Engineering and AI: Previous work bridging the gap between engineering and AI expertise would be highly valuable.
• Industry Collaboration: Prior experience in bridging academic findings with industry solutions.

Timeline

Deadline for applications	15 February 2024 at 16:00
Confirmation interviews	w/c 18 February 2024 (TBC)

How to Apply

Applications may be submitted any time before the deadline.

• Sign up to Inkpath.  Then affiliate your account to C-DICE.  For more details on how, click here.
• Apply via Inkpath using Activity Code DSAB0018 or click the button above.
• When you sign up for the activity, you will receive a link to an online application form.
• You will need:
  • Application details (education & employment background)
  • Cover letter stating your available start date (max 500 words)
  • CV

Supporting documents to be uploaded to Inkpath Activity DSAB0018. Any questions about the role or support in the application process should be emailed to C-DICE at a.beierholm@cdice.ac.uk and cc: enquiries@cdice.ac.uk.

Please note that if you are successful, your supervisor will be contacted for a letter/email of support.