**Job Description**
This fully funded 4-year PhD project, in collaboration with Innospec, focuses on investigating how different catalysts influence the growth, structure, and performance of carbon nanotubes (CNTs). The project aims to enhance understanding of catalyst composition in controlling CNT morphology and purity, crucial for their application as conductive additives in lithium-ion battery electrodes. The research will involve synthesizing CNTs via chemical vapour deposition (CVD), characterizing them using advanced techniques, and evaluating their electrochemical performance in Li-ion cells, with an emphasis on optimizing experimental design using AI/machine learning.
**Skills & Abilities**
� Experience in nanomaterials synthesis and characterization (desirable)
� Interest in energy storage technologies
� Interest in machine learning applications in materials science
� Strong analytical and problem-solving skills
� Ability to work independently and collaboratively
**Qualifications**
Required Degree(s) in:
� Materials Science
� Chemistry
� Physics
� Chemical Engineering
� Related discipline
� A first-class or upper second-class degree (or equivalent)
**Experience**
Other:
� Experience in nanomaterials synthesis and characterization is desirable.
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