At a Glance
- Tasks: Lead research on optimising ceramic coatings using CFD and machine learning.
- Company: Join a world-class multidisciplinary team at the University of Leeds.
- Benefits: Collaborative environment with opportunities for publications and presentations.
- Other info: Exciting challenge with industry partners and excellent career growth.
- Why this job: Make a real impact in materials technology and innovate digital tools.
- Qualifications: PhD or submitted thesis in relevant engineering or science disciplines.
The predicted salary is between 35000 - 45000 £ per year.
Are you experienced in computational modelling of complex flows for materials technology and ceramic coatings? Do you want to join a world-class multidisciplinary team with industry partners? Are you looking for a new and exciting challenge to develop innovative digital tools combining CFD and machine learning to reduce manufacturing-induced deficiencies of ceramics?
We have a vacancy for an enthusiastic researcher with expertise in computational fluid dynamics (CFD), complex (non-Newtonian) flows, and machine learning knowledge to work with us in the Institute of Design, Robotics and Manufacturing (School of Mechanical Engineering, University of Leeds) and a local industry partner.
You will lead work on investigating and optimising the influence of compositional change, temperature, and humidity on the rheological behaviour of a ceramic slurry using CFD. Collaborating with other colleagues and the industrial partner, you will be defining a process window for the manufactured ceramic coatings by benchmarking surface quality, thickness, uniformity, and leakage, and subsequently developing machine learning algorithms to optimise the various parameters involved in the process.
You will collaborate closely with other researchers to develop new learning and to disseminate the project findings via publications and presentations.
As a Research Fellow, you will have a PhD (or have submitted your thesis before taking up the role), and a Bachelors or Masters degree in Mechanical Engineering, Aerospace Engineering, Maths/Computer Science, Materials Engineering or a related discipline.
To explore the post further or for any queries you may have, please contact: Dr Masoud Jabbari, Lecturer (Assistant Professor) Email: M.Jabbari@leeds.ac.uk
Research Fellow in Digital Twining of Ceramic Coating in Leeds employer: University of Leeds
Join the University of Leeds as a Research Fellow in Digital Twining of Ceramic Coating, where you will be part of a world-class multidisciplinary team dedicated to innovation in materials technology. Our vibrant work culture fosters collaboration and creativity, providing ample opportunities for professional growth through research and industry partnerships. Located in a dynamic academic environment, you will have access to cutting-edge resources and the chance to contribute to impactful projects that shape the future of ceramic coatings.
StudySmarter Expert Advice🤫
We think this is how you could land Research Fellow in Digital Twining of Ceramic Coating in Leeds
✨Tip Number 1
Network like a pro! Reach out to your connections in the field of materials technology and ceramic coatings. Attend industry events or webinars where you can meet potential collaborators or employers. Remember, it’s all about who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous work in computational modelling and machine learning. This could be a great way to demonstrate your expertise and make you stand out during interviews.
✨Tip Number 3
Prepare for those interviews! Research common questions related to CFD and complex flows, and practice your responses. We recommend doing mock interviews with friends or mentors to boost your confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive and take the initiative to apply directly.
We think you need these skills to ace Research Fellow in Digital Twining of Ceramic Coating in Leeds
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in computational modelling, CFD, and machine learning. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or research!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about this role and how your background makes you a perfect fit. We love enthusiasm, so let your passion for digital twinning and ceramics come through.
Showcase Collaboration Skills:Since this role involves working closely with a multidisciplinary team and industry partners, highlight any previous collaborative projects. We want to know how you’ve successfully worked with others to achieve common goals!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it’s super easy!
How to prepare for a job interview at University of Leeds
✨Know Your Stuff
Make sure you brush up on your knowledge of computational fluid dynamics (CFD) and complex flows. Be ready to discuss specific projects or experiences where you've applied these concepts, especially in relation to ceramic coatings. This will show that you're not just familiar with the theory but can also apply it practically.
✨Showcase Your Collaboration Skills
Since this role involves working closely with a multidisciplinary team and industry partners, be prepared to share examples of how you've successfully collaborated in the past. Highlight any experiences where you’ve worked with others to solve problems or achieve common goals, particularly in research settings.
✨Demonstrate Your Problem-Solving Abilities
Think about challenges you've faced in your previous research or projects, especially those related to manufacturing deficiencies in ceramics. Be ready to discuss how you approached these issues and what innovative solutions you implemented, particularly using machine learning or CFD techniques.
✨Prepare Questions for Them
Interviews are a two-way street! Prepare insightful questions about the team, the projects you'll be working on, and the expectations for the role. This shows your genuine interest in the position and helps you gauge if it's the right fit for you.
