ML Research Associate: Cryo-EM & Cell Imaging

Rosalind Franklin Institute; Harwell; On-site; GBP 36,000 - 43,000; Full time

Benefits offered by this job

Hybrid and flexible working

Health and wellbeing support

Generous pension (up to 18%)

Free on-site parking

Perkbox access

Cycle to Work Scheme

Canteen on campus

Job summary

The Rosalind Franklin Institute invites applications for a Research Associate to advance molecular mapping of cells using machine-learning methods on cryo-electron tomograms. You will work with both experimental and computational researchers to develop and validate new detection and classification approaches for proteins and macromolecular complexes.

The role requires a PhD or near-completion and offers opportunities for scientific independence within a collaborative, interdisciplinary team on

Qualifications

• PhD/DPhil (or equivalent) is required or expected at appointment.
• Experience with ML methods for imaging and cell analysis is preferred.
• Ability to work across experimental and computational teams.

Responsibilities

• Develop ML methods to detect and classify proteins in cryo-EM tomograms.
• Integrate structural, molecular and imaging data to guide analysis.
• Prepare datasets, evaluate methods and validate biological findings.
• Develop reproducible workflows and research software with documentation.
• Lead major contributions to outputs such as papers and presentations.
• Supervise students or visitors and foster scientific independence.

Skills

Machine learning

Python

Data analysis

Collaboration

Education

PhD/DPhil (or equivalent)

Tools

PyTorch/TensorFlow

Subtomogram analysis

Data visualization

Job description

The Rosalind Franklin Institute invites applications for a Research Associate to advance molecular mapping of cells using machine-learning methods on cryo-electron tomograms. You will work with both experimental and computational researchers to develop and validate new detection and classification approaches for proteins and macromolecular complexes.

The role requires a PhD or near-completion and offers opportunities for scientific independence within a collaborative, interdisciplinary team on