Postdoc: Cellulose Self-Assembly & ML-Driven Modelling

The University of Manchester; Manchester; On-site; GBP 42,000 - 52,000; Full time

Benefits offered by this job

Generous employer contribution pension

29 days annual leave

Ride to work and EV car scheme

Job summary

The University of Manchester invites applications for a senior postdoctoral position to perform molecular modelling of cellulose oligomers and study self-assembly in the plant cell wall. The successful candidate will also assist in supervising PhD/MSc students within Eichhorn’s wider group, including project supervision and safety.

The role combines machine learning, molecular dynamics, and high-performance computing (Isambard AI) to screen structures, analyse data, and contribute to manuscript

Qualifications

• Ph.D. in computational chemistry, computational materials science or a relevant discipline.
• Proven research skills.
• Scientific scripting / programming.
• Experience in molecular dynamics simulations of polymers.

Responsibilities

• Conduct high-quality and publishable research in molecular modelling of cellulose and related materials; implement, execute and analyse advanced simulations; utilise ML and HPC platforms.
• Analyse and interpret data; contribute to the scientific direction of the project.
• Prepare and present regular reports on research progress.

Skills

Proven research skills

Scientific scripting

Programming

Molecular dynamics simulations

Education

PhD in computational chemistry or computational materials science

Tools

Molecular modelling software

Job description

The University of Manchester invites applications for a senior postdoctoral position to perform molecular modelling of cellulose oligomers and study self-assembly in the plant cell wall. The successful candidate will also assist in supervising PhD/MSc students within Eichhorn’s wider group, including project supervision and safety.

The role combines machine learning, molecular dynamics, and high-performance computing (Isambard AI) to screen structures, analyse data, and contribute to manuscript