The National Institute of Education invites suitable applications for the position of Research Fellow on a 24-month contract at the Natural Sciences and Science Education.
Project Title: AI-Driven Materials Development for Sustainable Rare Earth Element Recovery Using Electrodialysis (AI-REE)
Project Introduction: This project focuses on developing sustainable and cost-effective technologies for rare earth element (REE) recovery. Rare earth elements are critical for renewable energy, electronics, and advanced technologies, but current recovery methods are expensive and energy-intensive. The project aims to improve electrodialysis (ED) for REE separation by developing advanced membranes and integrating AI-driven optimization techniques. By combining materials innovation with machine learning, the project seeks to enhance selectivity, reduce energy consumption, and lower overall system costs for scalable and sustainable REE recovery.
Requirements:
Education
- PhD in Chemical Engineering, Materials Science & Engineering, Chemistry, Electrochemistry, or Data Science/AI with a strong background in materials applications
Technical Skills & Knowledge
- Experience in membrane fabrication and nanomaterials
- Knowledge of electrodialysis, electrochemical systems, or ion transport processes
- Familiarity with surface functionalization techniques or polymer chemistry
- Experience in experimental design and materials characterization (SEM, TEM, XPS, FTIR, etc.)
- Programming skills (Python, MATLAB, or similar)
- Exposure to machine learning methods (e.g., Bayesian optimization, active learning) is an advantage
- Understanding of techno-economic analysis is a plus
Personal Attributes
- Strong analytical and problem-solving skills
- Ability to work independently and in interdisciplinary teams
- Proactive, self-motivated, and research-driven
- Strong written and verbal communication skills
- Interest in sustainable technologies and translational research
Responsibilities:
- Design and fabricate membranes
- Conduct electrodialysis experiments for separation and performance benchmarking
- Develop and implement AI-driven optimization workflows (Bayesian optimization, active learning)
- Analyze membrane selectivity, stability, ion transport, and energy efficiency
- Contribute to techno-economic evaluation of the developed system
- Prepare research reports, journal publications, and conference presentations
- Collaborate with computational scientist
- Other duties assigned by Principal Investigator
Application
Applicants (external and internal) will apply via Workday. We regret that only shortlisted candidates will be notified.
Closing Date
Closing date for advertisements will be set to 14 calendar days from date of posting.
Hiring Institution: NIE