Postdoctoral Research Associate in Polymeric Materials Modelling

The University Of Manchester; Greater Manchester; On-site; GBP 38,000 - 48,000; Full time

Benefits offered by this job

Generous employer contribution pension

29 days annual leave + holidays

Ride to work and EV car scheme

Job summary

The University of Manchester invites applications for a senior postdoctoral position to conduct molecular modelling of cellulose oligomers and study self-assembly in plant cell walls. The successful candidate will also support day-to-day supervision of PhD and MSc students in Eichhorn's group and contribute to manuscript preparation.

The role combines advanced simulations, machine learning and high performance computing (Isambard AI) to screen structures, with opportunities to lead

Qualifications

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

Responsibilities

• Conduct high-quality research in molecular modelling of cellulose and related materials using advanced simulations and ML.
• Analyse data and influence the scientific direction of the project.
• Prepare regular progress reports and contribute to manuscripts.

Skills

Molecular modelling

Computational chemistry

Machine learning

Programming

Education

PhD in computational chemistry or related

Tools

GROMACS

LAMMPS

Python

Job description

A senior postdoctoral position is available for an ambitious individual to carry out the molecular modelling of cellulose oligomers investigating the self-assembly of the polymer in the plant cell wall. The senior postdoctoral assistant will also assist another postdoctoral researcher in the day-to-day supervisorial activities for Eichhorn's wider group of diverse PhD and MSc students, including project supervision, health and safety, and assistance with the drafting of manuscripts.

The successful applicant will undertake a fundamental study of the assembly of cellulose, using a unique approach of cellulose oligomers that have surfactant‑like properties. There have many recent attempts to synthesize cellulose analogues in the laboratory, through self‑assembly methods using enzymatic produced oligomeric forms. This work will pave the way for the practical assembly of cellulose oligomeric forms by screening large arrays of structures with different moieties and charges. To effectively do this, the postdoctoral researcher will combine machine learning, molecular dynamics simulations and high performance computing (Isambard AI).

Applicants must have a PhD in an appropriate area of computational chemistry or a related discipline and experience in the molecular modelling of polymers, polysaccharides, and preferably cellulose. Informal enquiries are welcome and should be made to Steve Eichhorn (Email: [e-mail]).

You will be responsible for:

• The conducting of high-quality and publishable research in the area of the molecular modelling of cellulose and related materials e.g. other plant cell wall polymers. This will involve the implementation, execution and analysis of advanced molecular simulations, the use of machine learning techniques and deployment on state‑of‑the‑art high performance computing platforms. Through interaction with the PI and other members of the team, contributing proactively to the development, progression and execution of the project
• Analysing and interpreting data and make a significant input to the scientific direction of the project
• Preparation and presentation of regular reports on research progress

We welcome candidates who bring diverse perspectives, experiences, and approaches to their work.

About You

We encourage applications from individuals with a wide range of backgrounds and experiences. You should demonstrate:

Essential Criteria:

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

Desirable Criteria:

• Molecular modelling and simulation experience during PhD
• Ability to present complex information effectively to a range of audiences
• Experience of manipulating and visualising large datasets

We value transferable skills and real‑world experience as much as formal qualifications.

Our benefits include:

• Generous employer contribution pension
• 29 days annual leave plus bank holidays, along with Christmas closure
• Ride to work and EV car scheme available

For more information, please see University of Manchester Benefits. You can also find information on our Flexible and Hybrid working here.

We are an open place of enquiry and challenge. We embrace and celebrate difference, diversity and debate, and we pride ourselves on being a place of education, learning and community where we are able, within the law, to question and test received wisdom, express new ideas and explore controversial or unpopular topics and opinions. Find out more from our Freedom of Speech Policy.

Enquiries about the role, shortlisting and interviews

Name: Professor Steve Eichhorn

Email Address: [e-mail]

General enquiries and administrative support

[e-mail]

Technical and job portal support

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