Research Associate - ML for Bio-Renewable Materials

Cambridge University Department of Chemical Engineering and Biotechnology; Cambridge; On-site; GBP 36,000 - 44,000; Full time

Job summary

The Cambridge University Department of Chemical Engineering and Biotechnology invites applications for a post-doctoral research fellow to join the VALUED project focusing on ML-assisted experimentation for functional materials derived from bio-renewable resources. The successful candidate will work under Prof.

Alexei Lapkin at the Innovation Centre in Digital Molecular Technologies (IDMT) and collaborate with Imperial College London, University of Bristol and Cambridge groups.

Qualifications

• Experience with high-throughput chemical experimentation.
• Ability to develop and validate predictive machine learning models for chemical problems.
• Strong collaboration and communication skills for multi-institutional projects.

Responsibilities

• Develop ML-assisted experimentation workflows for functional materials from bio-renewable resources.
• Create and evaluate predictive models to support high-throughput experiments and materials development.
• Collaborate with iDMT researchers and partners (Imperial College London, University of Bristol and Cambridge teams) to advance project goals.

Skills

High-throughput experiments

Predictive ML models

Education

PhD in a related field

Job description

The Cambridge University Department of Chemical Engineering and Biotechnology invites applications for a post-doctoral research fellow to join the VALUED project focusing on ML-assisted experimentation for functional materials derived from bio-renewable resources. The successful candidate will work under Prof.

Alexei Lapkin at the Innovation Centre in Digital Molecular Technologies (IDMT) and collaborate with Imperial College London, University of Bristol and Cambridge groups.