PhD Studentship: Plant Engineering & Single-Cell Genomics

University of East Anglia; Norwich; On-site; GBP 22,000 - 23,000; Full time

Benefits offered by this job

Stipend £21,805 per year

Research Training Support Grant £5,000

Fees paid (tuition)

Job summary

University of East Anglia is offering a PhD opportunity with the Guiziou Group at the Earlham Institute to apply engineering biology and single-cell genomic technology to understand lateral root initiation. You will build and optimise integrase-based genetic circuits in Arabidopsis and analyse them with fluorescence microscopy to reveal gene expression order in founder cells.

You will combine single-cell RNA sequencing with FACS to determine cell states in precise founder cell subpopulations,

Qualifications

• Undergraduate with a strong interest in engineering biology and plant science.
• Experience or coursework in molecular biology and microscopy valued.
• Interest in integrating DNA-based recording with single-cell approaches.

Responsibilities

• Build and optimise integrase-based genetic circuits in Arabidopsis.
• Analyse fluorescence to study gene expression timing and order.
• Use single-cell RNA sequencing (with FACS) to profile founder cell subpopulations.
• Develop critical thinking and scientific independence through the project.

Skills

Engineering biology

Plant biology

Single-cell RNA-seq

Arabidopsis genetics

Fluorescence microscopy

FACS

Genetic circuits

DNA-based recorders

Education

Undergraduate with strong background in engineering biology or plant science

Tools

Arabidopsis transformation

Single-cell sequencing

Protoplasting

Job description

University of East Anglia is offering a PhD opportunity with the Guiziou Group at the Earlham Institute to apply engineering biology and single-cell genomic technology to understand lateral root initiation. You will build and optimise integrase-based genetic circuits in Arabidopsis and analyse them with fluorescence microscopy to reveal gene expression order in founder cells.

You will combine single-cell RNA sequencing with FACS to determine cell states in precise founder cell subpopulations,