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Design of advanced coding and random access techniques for DNA storage

Project Description

Start date: October 2020
Duration: 3 years (full time)
Location: Colchester Campus
Based in: School of Computer Science and Electronic Engineering (in collaboration with School of Life Sciences and Department of Mathematical Sciences)

The unprecedented growth of digital information creates an increasingly growing demand for new ways of data storage.

DNA molecules can be an excellent medium for data storage, due to its potentially high information density (over 1000 millions gigabyte of data per mm3) and extreme durability (half-life of over 500 years).

The project

This project aims to develop efficient error-correcting codes (ECCs) and random access techniques for DNA storage.

By viewing DNA storage as a communication channel, we will design robust ECCs and their associated decoding schemes to combat the errors (e.g., insertion, deletion, and substitution) that arise in DNA synthesis and sequencing processes.

A key research problem we will address is how to carefully tailor ECCs to match to the specific characteristics of modern bio-chemical machines and processes.

Proposed ECCs will be optimised by DNA data analysis using modern machine learning algorithms (such as convolutional neural network and deep learning).

We will design uncorrelated DNA addresses (primers) to enable accurate random access of a desired data file in large sized DNA storage. Orthogonal sequence design approaches for wireless communications may be modified to design such uncorrelated primers.
We will also carry out hands-on experiments for channel measurement and validation of the proposed schemes.


Dr Zilong Liu – Lead Supervisor
Dr Nikolaos Thomos – Co-Supervisor
Professor Alex Dumbrell – Co-Supervisor
Dr Jessica Claridge – Co-Supervisor


The candidate is required to have a degree in electrical engineering with solid background in mathematics.
The candidate is also expected to have basic knowledge from biochemistry and have experience in hands-on lab experiments.

How to apply

You can apply for this postgraduate research opportunity online (
Please include your CV, covering letter, personal statement, and transcripts of UG and Masters degrees in your application.
The University has moved to requiring only one reference for PhD applications and these can be received after a conditional offer has been made so the absence of these will not hold up the recruitment process.

Find out more about this studentship and information on how to apply on our website (

Funding Notes

A full Home/EU fee waiver or equivalent fee discount for overseas students (£5,103 in 2020-21) (further fee details - international students will need to pay the balance of their fees) plus a doctoral stipend equivalent to the RCUK Minimum Doctoral Stipend (£15,009 in 2019-20, stipend for 2020-21 tbc).

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