The Sainsbury Laboratory | Pre-doctoral Research Assistant -…

Position Overview

We are seeking a motivated and innovative pre-doctoral research assistant to join our computational biology lab at The Sainsbury Laboratory. This position offers an excellent opportunity for recent graduates with a bachelor's degree who are interested in pursuing a PhD in the future and want to gain valuable research experience at the intersection of computational biology, machine vision, and lab automation.

About Our Lab

Our research group focuses on plant-microbe interactions using computational and experimental approaches. We develop cutting-edge tools and methods to understand the complex dynamics between plants and their microbial communities, with applications in sustainable agriculture and plant health.

Project Description

The successful candidate will work on an exciting project developing machine vision and lab automation systems using Raspberry Pi computers and cameras. You will create innovative tools that enable:

Continuous, non-invasive monitoring of microbial growth inside incubators
Automated analysis of plant growth and development in controlled environments (growth rooms and greenhouses)
Development of customized imaging solutions for plant-microbe interaction studies
Implementation of machine learning algorithms for image analysis and data interpretation

This project sits at the interface of biology, computer science, and engineering, offering a unique opportunity to develop interdisciplinary skills valuable for a future research career.

Duration: This is a 1-year position
Salary: TSL Grade 3 spine point 11 £23,881
Start Date: Available immediately, with some flexibility.
Closing Date: Application review will take place on the 15^th May 2025. The vacancy will be open until filled or 15^th June 2025, whichever comes sooner.

Responsibilities

Design, build, and test Raspberry Pi-based imaging systems for laboratory use
Develop software for image acquisition, processing, and analysis
Implement machine learning approaches for automated phenotyping
Collaborate with biologists to ensure systems meet research needs
Document development process and create user guides
Present findings at lab meetings and potentially at conferences
Contribute to publications and grant applications as appropriate

Required Qualifications

Bachelor's degree in Computer Science, Bioinformatics, Computational Biology, Bioengineering, or a related field
Programming experience in Python or similar languages
Interest in machine vision and image analysis
Basic understanding of biological systems, particularly plant biology
Strong problem-solving skills and attention to detail
Excellent communication skills and ability to work in a collaborative environment

Desired Qualifications

Experience with Raspberry Pi or similar single-board computers
Knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch)
Familiarity with computer vision libraries (e.g., OpenCV)
Previous laboratory research experience
Knowledge of plant-microbe interactions
Experience with version control systems (e.g., Git)

Benefits

Hands-on experience with cutting-edge research technologies
Mentorship from established researchers in the field
Opportunity to contribute to peer-reviewed publications
Development of technical and scientific skills applicable to PhD applications
Supportive and collaborative research environment
Exposure to both computational and experimental aspects of biological research

About The Sainsbury Laboratory (TSL)

TSL is an independent research institute renowned for world-leading plant health research for a sustainable future – reducing crop losses through fundamental scientific discoveries in molecular plant-microbe interactions. Located in Norwich in the county of Norfolk, one of the most beautiful and popular counties in the UK, TSL is a wonderful place to work and study.

We offer:

30 days of annual leave
A generous pension scheme
Professional development opportunities
A vibrant campus environment with cultural and recreational activities
A supportive, diverse, and inclusive workplace

Learn more about our Support for Staff on this page.

Application Process

If you would like to discuss the vacancy before applying, please contact:

The HR Department on: HR@TSL.ac.uk
To apply, click the Apply button on this page and submit the following:
CV (max. 2 pages)
Cover letter (max. 1 page) outlining your motivation and suitability for the role
Contact details for 2–3 referees

Please quote the reference code DM01-2025 in your application.