Battery Materials Scientist – AI-Driven Lab Innovation

Hong Kong Quantum AI Lab Ltd; Hong Kong; On-site; HKD 480,000 - 720,000; Full time

Benefits offered by this job

Multidisciplinary environment

Compensation commensurate with skills

Job summary

Hong Kong Quantum AI Lab (HKQAI) is an R&D centre jointly established by The University of Hong Kong and the California Institute of Technology.

You will conduct research on battery materials, such as electrodes and electrolytes for lithium-ion, sodium-ion and solid-state systems, and contribute to building self-driving laboratory capabilities. Experience with AI or robotics is not required, but would be an advantage.

Qualifications

• Postgraduate degree in materials science, chemistry, electrochemistry, physics or a related discipline from a top institution
• Familiarity with the design, preparation and testing of cathode, anode and/or solid electrolyte materials for lithium-ion or sodium-ion batteries
• Strong evidence of scientific excellence through research, publications or industrial R&D

Responsibilities

• Design and prepare battery electrode and electrolyte materials
• Evaluate their physical properties and electrochemical performance from materials-level testing through to pouch cells
• Drive scale-up of material preparation, including formulation optimisation and pilot process development
• Track research progress and industry trends in the battery field and bring them into our roadmap
• Collaborate with colleagues in AI and robotics to improve the capabilities of our self-driving laboratory

Skills

Battery materials design

Electrochemistry understanding

Education

Postgraduate degree in materials science, chemistry, electrochemistry, physics, or related discipline

Job description

Hong Kong Quantum AI Lab (HKQAI) is an R&D centre jointly established by The University of Hong Kong and the California Institute of Technology.

You will conduct research on battery materials, such as electrodes and electrolytes for lithium-ion, sodium-ion and solid-state systems, and contribute to building self-driving laboratory capabilities. Experience with AI or robotics is not required, but would be an advantage.