| Qualification Type: | PhD |
|---|---|
| Location: | Newcastle upon Tyne |
| Funding for: | UK Students |
| Funding amount: | £20,780 tax-free annual living allowance |
| Hours: | Full Time |
| Placed On: | 2nd April 2026 |
|---|---|
| Closes: | 27th April 2026 |
| Reference: | SNES304 |
Award Summary
3-year full-time PhD studentship (covering tuition fees, research costs and a tax-free annual living allowance of £20,780 (2025/26). Open to UK students only
Overview
As a community, GenerationResearch welcomes applications from students of all backgrounds but especially encourages underrepresented groups to apply.
We are seeking an enthusiastic and motivated graduate to join a research project focused on advancing plant health diagnostics through synthetic biology.
Plant pests and pathogens pose a major threat to agriculture, biodiversity, and biosecurity worldwide. Current diagnostic methods for quarantine pests often rely on complex, multi-step laboratory tests that are difficult to deploy in the field. This work will therefore be crucial in contributing to a new generation of diagnostics that may have implications for food security and conversation.
The successful student will explore innovative synthetic biology approaches to develop rapid, low-cost, and field-deployable tests for detecting quarantine pests/pathogens. You will evaluate technologies such as CRISPR-based systems, strand displacement reactions and cell-free biosensors, alongside novel mechanisms for sample processing. These aim to simplify nucleic acid detection and enable passive, self-reporting tests to transform surveillance and response strategies in plant health. Through systematic benchmarking this project will identify the most promising technologies for real-world application. The outcomes therefore contribute to UK biosecurity and inform diagnostic innovation. This PhD is a great opportunity for anyone interested in applied research, molecular biology, plant science, and working closely with a large UK life science company.
You will be supervised by Dr Jenny Tomlinson (Fera Science Ltd) and Dr Thomas Howard (Newcastle University), combining expertise in synthetic biology, molecular diagnostics, and plant health. You will be based at York Biotech Campus (Sand Hutton), with short visits to Newcastle for training and technology transfer.
Fera Science Ltd is a world-leading analytical laboratory with a strong track record in developing and deploying cutting-edge diagnostic technologies, including qPCR, LAMP, and high-throughput sequencing. Newcastle University offers a vibrant research environment with access to advanced synthetic biology and molecular biology facilities.
You will join a collaborative network spanning academia, government, and industry, with opportunities to engage with Defra and APHA stakeholders and contribute to national biosecurity strategy.
We will support you to learn key technical skills including in synthetic biology, in vitro diagnostic assays, and designing your own diagnostic experiments. Training will include access to Newcastle’s synthetic biology facilities and the analytical laboratories and quarantine facilities at Fera. Training can include workshops, seminars, and mentoring with colleagues who have the experience to help you in your studies. Have a look at some of the scientists who already work at Fera here. You will also have opportunities to present your work at national/international conferences and publish your work in peer-reviewed journals.
Number Of Awards
1
Start Date
21 September 2026
Award Duration
3 years
Application Closing Date
Monday 27 April 2026, midday
Sponsor
Supervisors
Dr Jenny Tomlinson (Fera Science Ltd)
Dr Thomas Howard (Newcastle University)
Eligibility Criteria
You must have, or expect to gain, a minimum 2:1 Honours degree or international equivalent in a subject relevant to the proposed PhD project (Biology and related disciplines).
Open to UK students only.
How To Apply
Apply for this PhD (Google Form). The closing date is Monday 27th April 2026, midday.
Contact Details
Type / Role:
Subject Area(s):
Location(s):