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- Tasks: Join us to develop cutting-edge digital twin solutions for smart manufacturing.
- Company: Be part of the Smart Nano NI consortium, a £40M project revolutionising advanced prototyping.
- Benefits: Enjoy a competitive salary and the chance to work on innovative technologies.
- Why this job: Tackle exciting data analytics challenges while contributing to impactful research in AI and manufacturing.
- Qualifications: Experience in digital twin technology and machine learning is essential.
- Other info: This is a full-time, fixed-term position until November 2027.
The predicted salary is between 32564 - 46761 £ per year.
Role: Research Associate / Research Fellow in Digital Twin-driven Predictive Maintenance for Smart Manufacturing (SmartNanoNI)
Department: School of Computing, Engineering and Intelligent Systems
Grade: Appointment at Research Associate level - Grade 6/7 (£32,564 - £46,761 per annum) or Research Fellow level - Grade 8 (£48,148 per annum) (Fixed-Term until 30th November 2027 / Full-time)
Job Purpose: The post holder will work within the Smart Nano manufacturing Northern Ireland (Smart Nano NI) consortium. Smart Nano NI is a £40M UKRI Strength in Places Fund (SIPF) multi-partner project, collaborating to develop game-changing advanced prototyping and smart manufacturing methods to deliver new intelligent technologies and facilitate fabrication of Smart Nano products.
This project offers an exciting opportunity for a researcher with experience in digital twin and machine learning, interested in understanding and addressing challenging data analytics problems. Working alongside the PI at the Intelligent Systems Research Centre (ISRC), the post holder will develop leading digital twin solutions including:
- Predictive modelling and simulation
- Data integration and management
- Human-virtual system interaction
- Machine learning algorithms
- Multi-objective co-evolutionary optimisation methods
to address some of the major challenges associated with a range of manufacturing challenges. The post holder will contribute to planning research, managing and analysing data, developing software and technologies for experiments and prototyping real-time digital twin and AI solutions, and will be expected to contribute to reporting results and publishing the results of the research in high-impact journal publications.
Appointment will be made at either Research Associate or Research Fellow level.
Closing date: 23rd March 2025 at 23:30
Research Associate / Research Fellow in Digital Twin-driven Predictive Maintenance for Smart Ma[...] employer: Webrecruit Ireland Ltd.
Contact Detail:
Webrecruit Ireland Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Associate / Research Fellow in Digital Twin-driven Predictive Maintenance for Smart Ma[...]
✨Tip Number 1
Familiarise yourself with the latest advancements in digital twin technology and predictive maintenance. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of smart manufacturing and digital twins. Attend relevant conferences, webinars, or workshops to make connections that could provide insights or even referrals for the position.
✨Tip Number 3
Prepare to discuss specific projects or experiences where you've applied machine learning or data analytics. Be ready to explain your thought process and the impact of your work, as this will demonstrate your practical knowledge and problem-solving skills.
✨Tip Number 4
Stay updated on the Smart Nano NI consortium's activities and achievements. Showing genuine interest in their projects and aligning your skills with their goals can set you apart from other candidates.
We think you need these skills to ace Research Associate / Research Fellow in Digital Twin-driven Predictive Maintenance for Smart Ma[...]
Some tips for your application 🫡
Understand the Role: Read the job description thoroughly to grasp the key responsibilities and required skills. Highlight your experience in digital twin technology, machine learning, and data analytics in your application.
Tailor Your CV: Customise your CV to reflect relevant experiences and skills that align with the job requirements. Emphasise any previous research projects or publications related to predictive maintenance and smart manufacturing.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for the field and explains why you are a great fit for the role. Mention specific projects or experiences that demonstrate your expertise in digital twin solutions and data management.
Proofread Your Application: Before submitting, carefully proofread your application materials for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism.
How to prepare for a job interview at Webrecruit Ireland Ltd.
✨Showcase Your Technical Skills
Make sure to highlight your experience with digital twin technology and machine learning during the interview. Be prepared to discuss specific projects you've worked on, the challenges you faced, and how you overcame them.
✨Understand the Project Goals
Familiarise yourself with the Smart Nano NI project and its objectives. Demonstrating knowledge about their goals and how your skills can contribute will show your genuine interest in the role.
✨Prepare for Problem-Solving Questions
Expect questions that assess your analytical thinking and problem-solving abilities. Practice articulating your thought process when tackling complex data analytics problems, as this is crucial for the role.
✨Emphasise Collaboration and Communication
Since the role involves working within a consortium, highlight your teamwork and communication skills. Share examples of how you've successfully collaborated with others in past projects, especially in research settings.
