The University of Birmingham is offering a fully funded four-year PhD studentship within the School of Engineering. This research project focuses on developing a high-throughput experimental approach to understand the rules governing EXPAR (isothermal DNA amplification) using statistical design and machine learning.
PhD Studentship: Learning the Kinetic Rules of DNA Amplification through High-Throughput EXPAR and Machine Learning
Scholarship Overview
| Institution | University of Birmingham |
| Department | School of Engineering |
| Designation | PhD Studentship |
| Research Area | DNA Amplification, Machine Learning, Bioengineering |
| Location | Birmingham, UK |
| Funding Amount | £21,805 annual stipend + research consumables |
| Closing Date | 23rd November 2026 |
Research Area
The project sits at the intersection of Molecular Biology, Engineering, and Data Science. It involves studying kinetic rules of DNA amplification, high-throughput experimentation, Bayesian optimization, and machine learning.
Location
University of Birmingham, School of Engineering, Birmingham, United Kingdom.
Eligibility/Qualification
- Student Status: Open to UK Students.
- Qualification: Applicants should hold or expect to obtain a high-quality honors degree (or equivalent) in a relevant engineering or science discipline.
- Skills: Interest in both experimental laboratory work and computational data analysis/machine learning.
Scholarship Description
EXPAR is a rapid isothermal DNA amplification reaction, but its performance varies significantly based on DNA sequence and environmental conditions. This PhD project aims to move beyond empirical optimization by establishing quantitative design rules. The successful candidate will:
- Measure amplification curves across diverse DNA sequences.
- Systematically vary polymerase/nicking enzyme concentrations, buffers, and temperatures.
- Utilize Statistical Design of Experiments, Bayesian optimization, and machine learning to identify critical factors.
- Test sequence-kinetic relationships using Single-nucleotide variants (SNVs) to ensure model accuracy.
The project is supervised by Dr Robert E Simpson and is funded through the MIBTP, providing a tax-free annual stipend of £21,805 (2026/27 rate), tuition fees, and approximately £4,500 per year for research consumables and travel.
How to Apply
Interested candidates should review the project details and supervisor information via the official MIBTP portal. Applications must be submitted through the university’s recruitment system.
For more information regarding the supervisor, visit: Dr Robert E Simpson Profile.
Last Date for Apply
The deadline for applications is 23rd November 2026.
Apply Link
Candidates can apply for this position through the following link: Apply Now
