Computational Structural Biologist – In Situ Cryo-ET

The Rosalind Franklin Institute; East Hagbourne; Hybrid; GBP 35,000 - 42,000; Full time

Benefits offered by this job

Holidays and personal leave

Pension scheme (employer’s up to 18%)

Group Life Assurance

Cycle to Work Scheme

Hybrid and flexible working

On-site parking

Perkbox access

Staff wellbeing support

Job summary

The Rosalind Franklin Institute invites a postdoctoral research associate to develop methods for in-situ structure reconstruction from human tissue data. You will lead computational approaches and collaborate with Imperial, UCL, and Oxford to advance cryo-electron tomography analyses.

Applicants should hold a PhD and have experience with structure determination pipelines, data interpretation, and scientific dissemination. Hybrid working and development opportunities are offered.

Qualifications

• PhD/DPhil in a relevant field or equivalent.
• Demonstrated expertise in cryo-electron tomography or related tools.
• Experience leading a research team or supervising junior researchers.

Responsibilities

• Develop and streamline computational approaches for in-situ structure determination from tissue sources.
• Lead collaborations with clinical partners to prepare tissues for cryo-ET.
• Design experiments, analyse data, and deliver research outputs (papers, patents, talks).
• Collaborate across Franklin's Challenges and contribute to project deliverables.

Skills

Cryo-EM data analysis

In-situ structure determination

Leadership in team settings

Communication of research outputs

Education

PhD in a relevant field

Tools

Cryo-EM pipelines

Macromolecular modelling

Job description

The Rosalind Franklin Institute invites a postdoctoral research associate to develop methods for in-situ structure reconstruction from human tissue data. You will lead computational approaches and collaborate with Imperial, UCL, and Oxford to advance cryo-electron tomography analyses.

Applicants should hold a PhD and have experience with structure determination pipelines, data interpretation, and scientific dissemination. Hybrid working and development opportunities are offered.