Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop AI methods for predicting crystal structures in materials discovery.
- Company: Join the University of Liverpool, a leader in innovative research.
- Benefits: Work in a diverse team with opportunities for knowledge sharing and training.
- Why this job: Be part of cutting-edge AI projects that impact materials science and robotics.
- Qualifications: PhD in relevant fields; expertise in AI and machine learning is essential.
- Other info: This position is available for two years, focusing on collaborative research.
The predicted salary is between 28800 - 48000 £ per year.
This post will develop artificial intelligence methods for the prediction of crystal structure, the critical step in materials prediction for discovery. It will develop and apply new ML approaches to crystal structure prediction.
Based at the University of Liverpool, you will have a key role in one of the forerunner projects of AlChemy, namely "Human in the Loop", which aims at integrating cutting-edge AI technologies with Robotics in accelerating the discovery and synthesis of new materials. You should have a PhD in a relevant field (Computer Science, Mathematics are most likely to fit the role but we are open to Chemistry, Materials Science, Chemical Engineering, etc.), expertise in cutting-edge AI and machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role.
This post would be ideal for an ambitious and innovative scientist who is driven, enjoys working in a diverse team, keen to share knowledge and eager to train others in the group. In this project, engagement with chemists and materials scientists is essential to ensure that the developed methods make optimal use of domain expertise and integrate fully into "human in the loop" workflows.
This post is available for two years.
Keywords: Geometric Deep Learning, in particular Graph Neural Networks, Deep Reinforcement Learning, Generative Modelling, in particular Denoising Diffusions, Combinatorial Optimisation
Jobs.ac.uk
Research Fellow Artificial Intelligence for Materials Discovery (AIChemy) Grade 7 employer: University of Liverpool
Contact Detail:
University of Liverpool Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Fellow Artificial Intelligence for Materials Discovery (AIChemy) Grade 7
✨Tip Number 1
Familiarize yourself with the latest advancements in AI and machine learning, especially in the context of materials discovery. Being able to discuss recent papers or breakthroughs during your interview can demonstrate your passion and knowledge in the field.
✨Tip Number 2
Engage with the research community by attending relevant conferences or workshops. Networking with professionals in the field can provide insights into current challenges and trends, which you can reference in your discussions with us.
✨Tip Number 3
Showcase your collaborative skills by highlighting any previous experiences where you worked in diverse teams. Emphasizing your ability to communicate effectively with chemists and materials scientists will be crucial for this role.
✨Tip Number 4
Prepare to discuss how you would integrate AI technologies with robotics in the context of materials discovery. Having a clear vision of how these elements can work together will set you apart as a candidate who is not only innovative but also practical.
We think you need these skills to ace Research Fellow Artificial Intelligence for Materials Discovery (AIChemy) Grade 7
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the key responsibilities and requirements. Highlight your relevant experience in AI, machine learning, and any knowledge of materials science or chemistry.
Tailor Your CV: Customize your CV to emphasize your PhD and any relevant projects or research that align with the role. Include specific examples of your work with AI methods, particularly in geometric deep learning or reinforcement learning.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for the field and your innovative approach to research. Mention your eagerness to collaborate with chemists and materials scientists, and how you can contribute to the 'Human in the Loop' project.
Highlight Teamwork and Communication Skills: Since the role involves working in a diverse team, emphasize your ability to share knowledge and train others. Provide examples of past experiences where you successfully collaborated with others in a research setting.
How to prepare for a job interview at University of Liverpool
✨Showcase Your AI Expertise
Make sure to highlight your experience with cutting-edge AI and machine learning techniques. Be prepared to discuss specific projects where you've applied these methods, especially in the context of crystal structure prediction or materials discovery.
✨Demonstrate Collaborative Spirit
Since this role involves working closely with chemists and materials scientists, emphasize your ability to work in diverse teams. Share examples of how you've successfully collaborated with professionals from different backgrounds in past projects.
✨Prepare for Technical Questions
Expect technical questions related to Geometric Deep Learning, Graph Neural Networks, and other relevant methodologies. Brush up on these topics and be ready to explain complex concepts in a clear and concise manner.
✨Express Your Ambition and Innovation
This position is ideal for an ambitious scientist. Convey your passion for innovation and your eagerness to contribute to groundbreaking research. Discuss any ideas you have for future projects or improvements in the field of materials discovery.
