construction.
You will be responsible for:
- Develop simulation models by creating and validating advanced simulation models to replicate dynamic prefabricated construction sites
- Enhance prefabricated construction processes by identifying areas of inefficiency, safety risks and design mitigation strategies, and align them with industry standards
- Optimise task allocation by designing strategies to streamline task design and allocation to improve safety, productivity, and environmental sustainability
- Collaborate with stakeholders by engaging with academics and industry partners to refine models, strategies, and project outputs
- Disseminate project findings by publishing results in academic journals, generate industry reports, and lead workshops
We welcome candidates who bring diverse perspectives, experiences, and approaches to their work.
About you
We encourage applications from individuals with a wide range of backgrounds and experiences. You should demonstrate:
Essential criteria:
- Candidates should hold a PhD (or equivalent) in a relevant field such as Mechanical Engineering, Aerospace Engineering, Electrical & Electronics Engineering, Computer Science, Digital Construction or a related discipline
- Demonstrable experience in modelling, simulation, and optimisation of industrial workflows and processes, especially in advanced manufacturing and/or prefabricated construction
- Proficiency in systems design and optimisation, programming, and practical implementation, with a focus on advanced manufacturing in construction
- Strong skills in simulation methodologies
- Excellent communication and interpersonal skills
Desirable criteria:
- Familiarity with machine learning algorithms and artificial intelligence as applied to advanced manufacturing
- Understanding of organisational psychology principles related to advanced manufacturing and prefabricated construction
- Knowledge of construction workflows, equipment, and safety protocols
- Familiarity with IoT devices, digital twinning, and sensors for advanced manufacturing applications in construction
- Experience in mentoring or supervising workers, junior researchers, or students
We value transferable skills and real-world experience as much as formal qualifications.
Our benefits include:
- Generous employer contribution pension
- 29 days annual leave plus bank holidays, along with Christmas closure
- Ride to work and EV car scheme available
For more information, please seeUniversity of Manchester Benefits. You can also find information on our Flexible and Hybrid workinghere.
We are an open place of enquiry and challenge. We embrace and celebrate difference, diversity and debate, and we pride ourselves on being a place of education, learning and community where we are able, within the law, to question and test received wisdom, express new ideas and explore controversial or unpopular topics and opinions. Find out more from ourFreedom of Speech Policy.
Enquiries about therole, shortlisting and interviews
Name: Dr. Akilu Yunusa-Kaltungo and Dr Clara Cheung
Email address:
General enquiries and administrative support
recruitmentservices.people@manchester.ac.uk
Technical and job portal support jobseekersupport.jobtrain.co.uk/support/home
Applications close at midnight on the closing date.
£37,694 to £46,049 per annum depending on experience
