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- Tasks: Join a team to develop AI methods for predicting crystal structures in materials discovery.
- Company: Be part of a cutting-edge partnership between the University of Liverpool and top institutions.
- Benefits: Enjoy a competitive salary, diverse work environment, and opportunities for professional growth.
- Why this job: Work on innovative projects that integrate AI with chemistry, making a real impact in materials science.
- Qualifications: PhD in relevant fields; expertise in AI and machine learning is essential.
- Other info: This role promotes diversity and welcomes applicants from all backgrounds.
The predicted salary is between 33900 - 39600 £ per year.
A Research Fellow position is available in the group of Professor M. J. Rosseinsky OBE FRS to work in a team of computer scientists and materials chemists funded by the AlChemy. AI in Chemistry Hub: AlChemy is a new partnership between the University of Liverpool, Imperial College London and a large consortium of academic and industrial partners. AIChemy has been funded to promote the development of novel AI, alongside the increased uptake of AI amongst the chemistry community.
The consortium brings together experts across AI and both experimental and computational chemistry and this Hub will promote connectivity of the broader community, training, networking, as well as state-of-the-art research. 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.
Commitment to Diversity: The University of Liverpool is committed to enhancing workforce diversity. We actively seek to attract, develop, and retain colleagues with diverse backgrounds and perspectives. We welcome applications from all genders/gender identities, Black, Asian, or Minority Ethnic backgrounds, individuals living with a disability, and members of the LGBTQIA+ community.
Research Fellow in Artificial Intelligence for Materials Discovery (AIchemy) - Grade 7 employer: Chemistry Guide
Contact Detail:
Chemistry Guide Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Fellow in Artificial Intelligence for Materials Discovery (AIchemy) - Grade 7
✨Tip Number 1
Familiarise yourself with the latest advancements in AI and machine learning, particularly in the context of materials discovery. 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 by attending relevant conferences or workshops. Engaging with experts can provide insights into the latest research trends and may even lead to valuable connections that could support your application.
✨Tip Number 3
Showcase your collaborative skills by discussing any previous team projects or interdisciplinary work you've been involved in. Highlighting your ability to work effectively with chemists and materials scientists will demonstrate your fit for the 'Human in the Loop' aspect of the role.
✨Tip Number 4
Prepare to discuss how you would approach integrating AI technologies with robotics in materials discovery. Having a clear vision of how these elements can work together will set you apart as a candidate who is not only knowledgeable but also innovative.
We think you need these skills to ace Research Fellow in Artificial Intelligence for Materials Discovery (AIchemy) - Grade 7
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI, machine learning, and any work related to materials chemistry. Use specific examples that demonstrate your expertise and how it aligns with the role.
Craft a Compelling Cover Letter: Write a cover letter that not only outlines your qualifications but also expresses your enthusiasm for the project and the team. Mention your understanding of the 'Human in the Loop' concept and how you can contribute to it.
Highlight Relevant Skills: In your application, emphasise your skills in geometric deep learning, graph neural networks, and any other relevant methodologies mentioned in the job description. Be specific about your experience with these technologies.
Showcase Collaborative Experience: Since the role involves working in a diverse team, include examples of past collaborative projects. Highlight your ability to engage with chemists and materials scientists, showcasing your communication skills and teamwork.
How to prepare for a job interview at Chemistry Guide
✨Showcase Your Technical Skills
Be prepared to discuss your expertise in AI and machine learning. Highlight specific projects or research where you've applied these skills, especially in relation to crystal structure prediction or materials chemistry.
✨Demonstrate Team Collaboration
Since this role involves working closely with chemists and materials scientists, share examples of how you've successfully collaborated in diverse teams. Emphasise your ability to communicate complex ideas clearly to non-experts.
✨Engage with the 'Human in the Loop' Concept
Familiarise yourself with the 'Human in the Loop' approach and be ready to discuss how you would integrate AI technologies with human expertise. This shows your understanding of the project's goals and your innovative thinking.
✨Commitment to Diversity
Reflect on how your background and experiences contribute to diversity in the workplace. Be ready to discuss how you can support an inclusive environment, aligning with the University of Liverpool's commitment to enhancing workforce diversity.
