At a Glance
- Tasks: Conduct AI-driven ligand discovery for metal recovery from lithium batteries.
- Company: Join a leading research group at the University of Leeds.
- Benefits: Receive a competitive tax-free maintenance grant and full fees for 3.5 years.
- Other info: Collaborate with top researchers and gain hands-on experience in cutting-edge science.
- Why this job: Make a real impact in sustainable technology and environmental chemistry.
- Qualifications: First or Upper Second Class UK Bachelor (Honours) in relevant fields.
The predicted salary is between 19237 - 19237 £ per year.
Eligibility: UK Applicants only
Funding: A highly competitive EPSRC Doctoral Training Partnership Studentship, in partnership with GoldenKeys Hi-tech Ltd, offering the award of fees, together with a tax-free maintenance grant of £19,237 for 3.5 years.
Lead Supervisor’s full name & email address: Professor Bao Nguyen – b.nguyen@leeds.ac.uk
Co-supervisor name(s): Professor Patrick McGowan – p.c.mcgowan@leeds.ac.uk
Project summary: Ligand/material discovery has been carried out through laborious trial-and-error approaches. Recent advances in high throughput computational chemistry and AI/Machine Learning provided us with a more efficient, in silico approach to develop new ligands for functional materials and catalysis. We aim to extend the Big Data/high throughput DFT methodology in Nguyen group to carry out ligand discovery in silico for Li, Mn, Co and Ni recovery from spent lithium batteries. This will take advantage of experience in Nguyen group on using AI and Machine Learning for ligand discovery in catalysis.
The student will analyse literature ligands for Li, Mn, Co and Ni using cheminformatics and data science techniques to identify the required features of successful ligands (i.e. high binding strength). These insights will inform an exhaustive search of the Cambridge Structural Database (CDS, 1.5M structures) for potential ligands and their performance will be evaluated with high throughput DFT calculations. The workflow will be automated with Python code developed in Nguyen group, in collaboration with DiLabio group at University of British Columbia, which will significantly speed up our workflow to minutes per ligands. The most successful ligands identified in silico will be prepared and validated experimentally. Further refinement of the lead ligands through rational design, computational evaluation, and experimental validation will be carried out. The successful and novel ligands will be developed into new commercial products for recovering these critical metals from spent lithium batteries.
References: Sci. Technol. 2023, 13, 2407-2420; ChemCatChem 2024, e202301475.
Please state your entry requirements plus any necessary or desired background: First or Upper Second Class UK Bachelor (Honours) or equivalent
Subject Area: Environmental Chemistry, Physical Chemistry, Synthetic Chemistry
AI-Driven Ligand Search for Metal Recovery in Li Batteries in Leeds employer: University of Leeds
As a leading institution in environmental chemistry and innovative research, we offer an exceptional opportunity for UK applicants to engage in cutting-edge AI-driven projects that contribute to sustainable metal recovery from lithium batteries. Our collaborative work culture fosters creativity and growth, supported by competitive funding and mentorship from esteemed professors, ensuring that students not only gain invaluable experience but also make meaningful contributions to the field. Located at the forefront of scientific advancement, our environment encourages exploration and the development of novel solutions to pressing global challenges.
StudySmarter Expert Advice🤫
We think this is how you could land AI-Driven Ligand Search for Metal Recovery in Li Batteries in Leeds
✨Tip Number 1
Network like a pro! Reach out to your professors, industry contacts, or even fellow students. They might know about opportunities that aren't advertised yet. Plus, a personal recommendation can go a long way!
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your knowledge about the project. Dive deep into the specifics of AI and ligand discovery, and be ready to discuss how your skills align with the role.
✨Tip Number 3
Don’t just apply anywhere; focus on roles that excite you! Use our website to find positions that match your interests in environmental chemistry and AI. Tailor your approach to show why you're the perfect fit.
✨Tip Number 4
Follow up after interviews! A quick thank-you email can keep you fresh in their minds. It shows your enthusiasm and professionalism, which can set you apart from other candidates.
We think you need these skills to ace AI-Driven Ligand Search for Metal Recovery in Li Batteries in Leeds
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your application to highlight how your skills and experiences align with the project. We want to see your passion for AI and chemistry shine through!
Showcase Relevant Experience:If you've worked on projects involving cheminformatics, data science, or computational chemistry, be sure to mention them! We love seeing how your background fits into our exciting research.
Be Clear and Concise:Keep your writing straightforward and to the point. We appreciate clarity, so avoid jargon unless it's necessary. Remember, we want to understand your ideas easily!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way to ensure it gets to us directly and helps us keep track of all applicants.
How to prepare for a job interview at University of Leeds
✨Know Your Stuff
Make sure you brush up on the latest advancements in AI and machine learning, especially as they relate to ligand discovery. Familiarise yourself with the Cambridge Structural Database and be ready to discuss how you would approach ligand analysis using cheminformatics.
✨Show Your Passion
Express your enthusiasm for environmental chemistry and the recovery of metals from lithium batteries. Share any relevant projects or experiences that highlight your commitment to this field, as it will resonate well with the interviewers.
✨Prepare Questions
Have a few thoughtful questions ready about the project and the team. This shows that you're genuinely interested and have done your homework. Ask about the specific methodologies used in the Nguyen group or how collaboration with the DiLabio group enhances the research.
✨Practice Makes Perfect
Conduct mock interviews with friends or mentors to get comfortable discussing your background and how it relates to the role. Focus on articulating your thoughts clearly, especially when explaining complex concepts like high throughput DFT calculations.
