New opportunity: AstraZeneca to fund Compass PhD project

Novel semi-supervised Bayesian learning to rapidly screen new oligonucleotide drugs for impurities.

This is an exciting opportunity to join Compass’ 4-year programme with integrated training in the statistical and computational techniques of Data Science. You will be part of a dynamic cohort of PhD researchers hosted in the historic Fry Building, which has recently undergone a £35 million refurbishment as the new home for Bristol’s School of Mathematics.

This fully-funded 4 year studentship covers:

  • tuition fees at UK rate
  • tax-free stipend of up £19,609 per year for living expenses and
  • equipment and travel allowance to support research related activities.

This opportunity is open to UK, EU, and international students. 

AstraZeneca is a global, science-led biopharmaceutical business whose innovative medicines are used by millions of patients worldwide. Oligonucleotide-based therapies are advanced novel interventions with the potential to provide a step-change in treatment for many. Nevertheless, as oligonucleotides are large complex molecules they are currently very difficult to profile for impurities, as the analysis is labour intensive and the data complexity is high.

About the Project

The aim of this PhD is to develop Bayesian data science methodology that does this automatically, accurately, and delivers statistical measures of certainty. The challenge is a mathematical one, and no chemistry, biology or pharmacological background is expected of the student. More specifically, we have large batches of mass spectrometry data that will enable us to learn how to characterise the known oglionucleotide signal and deconvolute it from a number of known and unknown impurities longitudinally, in a semi-supervised learning framework. This will allow us to confirm the overall consistency of the profile, identify any change patterns, trends over batches, and any correlation between impurities.

The end goal is to establish a data analytics pipeline and embed it as part of routine analysis in AstraZeneca, so impurities can be monitored more closely and more precisely. The knowledge can then be used to identify possible issues in manufacturing and improve process chemistry by pinpointing impurities associated with different steps of the drug synthesis. This project would also improve the overall understanding of oligonucleotides and therefore, serve as a key step towards establishing an advanced analytical platform.

Project Supervisor

The PhD will be supervised by statistical data scientist Prof Andrew Dowsey at Bristol in collaboration with AstraZeneca. Prof Dowsey’s group has extensive expertise and experience in Bayesian mass spectrometry analytics (e.g. Nature Comms Biology 2019Nature Scientific Reports 2016) and leads the development of the seaMass suite of tools for quantification and statistical analyses in mass spectrometry.

Application Deadline

Application Deadline is 5.00pm Friday 18 June 2021. Please quote ‘Compass/ AstraZeneca’ in the funding section of the application form and in your Personal Statement to ensure your application is reviewed correctly. Please follow the Compass application guidance.

Interviews are expected to be held in the week commencing 12 July.

Sparx joins as Compass’ newest industrial partner

The University of Bristol is today announcing a new supporter of Compass – the EPSRC Centre for Doctoral Training in Computational Statistics and Data Science. South West based learning technology company Sparx, has agreed to sponsor a PhD student’s research project which will investigate new approaches to longitudinal statistical modelling within school-based mathematics education.

Sparx, which is located in Exeter, develops maths learning tools to support teaching and learning in secondary education. As an evidence-led company, Sparx has invested heavily in researching how technology can support the teaching and learning of maths and worked closely with local schools. This new investment underlines their ongoing commitment to research.

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