Title: SCH34: Design of advanced coding and random access techniques for DNA storage
Funding: 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 (£15,285 in 2020-21).
Application deadline: Tuesday 31 March 2020
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)
This opportunity is now closed. View our open opportunities.
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).
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.
This PhD program will be in collaboration with Coding Theorist Prof Wai Ho Mow in Hong Kong University of Science and Technology (HKUST). The candidate will be encouraged to apply for an International Visiting Internship to HKUST for up to 6 months, during which an additional allowance of about USD 1,500 per month may be provided by HKUST as the internship organiser.
The award consists of a full Home/EU fee waiver or equivalent fee discount for overseas students (further fee details), a doctoral stipend equivalent to the Research Councils UK National Minimum Doctoral Stipend (£15,285 in 2020-21), plus £2,500 training bursary via Proficio funding, which may be used to cover the cost of advanced skills training including conference attendance and travel.
Lead supervisorSchool of Computer Science and Electronic Engineering, University of Essex
Zilong Liu is a Lecturer at the School of Computer Science and Electronic Engineering, University of Essex. From 2018 to 2019, he was a Senior Research Fellow at the 5G Innovation Centre (5GIC), University of Surrey. Prior moving to UK, he spent 9.5 years in the School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore. He is generally interested in coding and signal processing for various communication systems.
Co-supervisorSchool of Computer Science and Electronic Engineering, University of Essex
Nikolaos Thomos is a Reader in CSEE and the CSEE deputy director of research. Before that, he was senior researcher at EPFL, Switzerland. He was awarded the highly esteemed Ambizione career award from Swiss National Science Foundation (SNSF) in 2008 and 2011 for carrying out research on low computational complexity network coding for collaborative video streaming. His research interests include machine learning for communications, multimedia communications, network coding, and joint source and channel coding.
Co-supervisorSchool of Life Sciences, University of Essex
Alex Dumbrell is a Professor in School of Life Sciences since 2019. He received his PhD from University of York in 2006. His research interests include spatial and temporal patterns of biodiversity, next generation sequencing technology and bioinformatics in ecological research, and theoretical ecology (focus on models of biodiversity). He has co-authored over 50 journal papers, 7 books and 10 book chapters.
Co-supervisorDepartment of Mathematical Sciences, University of Essex
Jessica Claridge has been a Lecturer in the Mathematics Department and Essex Parthways Department at the University of Essex since 2016. She received a PhD in the Mathematics from Royal Holloway, University of London in 2017. Her research interests include combinatorics and applications in coding theory and information theory.
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.
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.
When you apply online you will be prompted to fill out several boxes in the form:
If you have any informal queries about this opportunity please email the lead supervisor, Dr Zilong Liu (firstname.lastname@example.org).
You can find the terms and conditions of this studentship here (PDF).