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.

Launch of industry-focused seminar series DataScience@Work

Compass is excited to announce the launch of the DataScience@work seminar series. This new seminar series invites speakers from external organisations to talk about their experiences as Data Scientists in industry, government and the third sector. The dual meaning of DataScience@work focuses talks on both the technical side of the speakers’ roles as well as working as part of a wider organisation, and building a career in data science.

Highlighting the importance of the new seminar series, Prof Nick Whiteley (Compass Director) says…

Prof Nick Whiteley addresses industry partners

Compass aims to develop scientific and professionally agility in its students. Our goal is to connect technical expertise in data science with experience of thinking, communicating and collaborating across disciplines and across sectors. In our new DataScience@Work seminar series, Compass partners from industry will share insights into the key role of Data Science within their organisations, their objectives and future outlook. This is a great opportunity for our students to learn about career trajectories beyond academia, helping shape their aspirations and personal goals for life beyond the PhD. I’m especially grateful to Adarga, CheckRisk, IBM Research, Improbable, and Shell for leading this first season of DataScience@Work and for their ongoing support for Compass.

For further information on the seminar series, including invited speakers to the 2020/21 session, see the DataScience@work page.


Skills for Interdisciplinary Research

To acknowledge the variety of sectors where data science research is relevant, in March 2021, the Compass students are undertaking a series of workshops led by the Bristol Doctoral College to explore Skills for Interdisciplinary Research.  Using the Vitae framework for researcher development, our colleague at BDC will introduce Compass students to the following topics:

Workshop 1: What is a doctorate? A brief history of doctorates in the UK, how they have changed in the past two decades, why CDTs?, what skills are needed now for a doctorate?

Workshop 2: Interdisciplinarity – the foundations. A practical case study on interdisciplinary postgraduate research at Bristol.

Workshop 3: Ways of knowing, part 1 – Positivism and ‘ologies! Deconstructing some of the terminology around knowledge and how we know what we know. Underpinning assumption – to know your own discipline, you need to step outside of it and see it as others do.

Workshop 4: Ways of knowing, part 2 – Social constructionism and qualitative approaches to research. In part 1 of ways of knowing, the ideal ‘science’ approach is objective and the researcher is detached from the subject of study; looking at other approaches where the role of research is integral to the research.

Workshop 5: Becoming a good researcher – research integrity and doctoral students. A look at how dilemmas in research can show us how research integrity is not just a case of right or wrong.

Workshop 6: Getting started with academic publishing. An introduction on the scholarly publishing pressure in contemporary research and it explores what that means in an interdisciplinary context.

Student Research Topics for 2020/21

This month, the Cohort 2 Compass students have started work on their mini projects and are establishing the direction of their own research within the CDT.

Supervised by the Institute for Statistical Science:

Anthony Stevenson will be working with Robert Allison on a project entitled Fast Bayesian Inference at Extreme Scale.  This project is in partnership with IBM Research.

Conor Crilly will be working with Oliver Johnson on a project entitled Statistical models for forecasting reliability. This project is in partnership with AWE.

Euan Enticott will be working with Matteo Fasiolo and Nick Whiteley on a project entitled Scalable Additive Models for Forecasting Electricity Demand and Renewable Production.  This project is in partnership with EDF.

Annie Gray will be working with Patrick Rubin-Delanchy and Nick Whiteley on a project entitled Exploratory data analysis of graph embeddings: exploiting manifold structure.

Ed Davis will be working with Dan Lawson and Patrick Rubin-Delanchy on a project entitled Graph embedding: time and space.  This project is in partnership with LV Insurance.

Conor Newton will be working with Henry Reeve and Ayalvadi Ganesh on a project entitled  Decentralised sequential decision making and learning.

The following projects are supervised in collaboration with the Institute for Statistical Science (IfSS) and our other internal partners at the University of Bristol:

Dan Ward will be working with Matteo Fasiolo (IfSS) and Mark Beaumont from the School of Biological Sciences on a project entitled Agent-based model calibration via regression-based synthetic likelihood. This project is in partnership with Improbable

Jack Simons will be working with Song Liu (IfSS) and Mark Beaumont (Biological Sciences) on a project entitled Novel Approaches to Approximate Bayesian Inference.

Georgie Mansell will be working with Haeran Cho (IfSS) and Andrew Dowsey from the School of Population Health Sciences and Bristol Veterinary School on a project entitled Statistical learning of quantitative data at scale to redefine biomarker discovery.  This project is in partnership with Sciex.

Shannon Williams will be working with Anthony Lee (IfSS) and Jeremy Phillips from the School of Earth Sciences on a project entitled Use and Comparison of Stochastic Simulations and Weather Patterns in probabilistic volcanic ash hazard assessments.

Sam Stockman  will be working with Dan Lawson (IfSS) and Maximillian Werner from the School of Geographical Sciences on a project entitled Machine Learning and Point Processes for Insights into Earthquakes and Volcanoes

New opportunity: a jointly funded studentship with FAI Farms

Compass is very excited to advertise this PhD studentship in collaboration with FAI Farms on a vision-based system for automated poultry welfare assessment through deep learning and Bayesian modelling.

About the Project

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.

FAI Farms

FAI Farms is a multi-disciplinary team working in partnership with farmers and food companies to provide practical solutions for climate and food security. FAI’s state-of-the-art strategic advice, data insight, and education services, are powered by science, technology and best practice. Our strategic and evidence-based approach is focused on driving meaningful improvements across supply chains, mitigating risks and realising long term business benefits for our partners.

The aim of this PhD project is to create a vision-based system for the automated assessment of chicken welfare for use in poultry farms. The welfare of broiler chickens is a key ethical and economic challenge for the sustainability of chicken meat production. The presentation of natural, positive behaviour is important to ensure a “good life” for livestock species as well as being an expectation for many consumers. At present there are no ways to measure this, with good welfare habitually defined as the absence of negative experience. In addition, automated tracking of individual birds is very challenging due to occlusion and complexity. In this project the student will instead harness and develop novel deep learning approaches that consider individual animals and their behaviours probabilistically within the context of local and general activity within the barn and wider flock. The inferred behaviour rates amongst the flock will then be integrated with on-farm production, health and environmental data through Bayesian time series modelling to identify risk factors for positive welfare, predict farms at risk of poor welfare, and suggest interventions that avoid this scenario.


Virtual Visiting Professor, Wei Biao Wu (University of Chicago): online colloquium on Wednesday 24 March

New advanced computing hardware for Compass students

As part of UKRI NPIF Talent Funding 2019/2020, Compass applied for additional hardware and now has an operational GPU node*, specifically designed for the needs of statistical and machine learning analysis and with priority for COMPASS students.

This will enable our students to more rapidly train a wide variety of powerful, state of the art models in machine learning. GPUs have been essential to the rise of deep learning which, in the past decade, has revolutionised machine learning, rendering previously impossible tasks in image and natural language processing surmountable.

*: Technical specifications: 4 x Nvidia RTX 2080Ti graphics cards 11GB memory, dual quad core Xeon 4112 CPUs, 96 GBytes RAM, 10 Gbit ethernet, 1 TB local drive.

IBM Research is newest Compass partner to sponsor PhD project

The University of Bristol is excited to announce IBM Research Europe as a new partner of Compass – the EPSRC Centre for Doctoral Training in Computational Statistics and Data Science. IBM scientists are collaborating with Prof. Robert Allison and Compass PhD student Anthony Stephenson, on a research project entitled Fast Bayesian Inference at Extreme Scale. The project’s aim is to extend Bayesian inference algorithms to the ‘extreme scales’ that many deep learning workloads occupy, by placing more focus on AI methodologies which furnish both an accurate prediction, and critically, a high-quality uncertainty representation for predictions.

For more than seven decades, IBM Research has defined the future of information technology with more than 3,000 researchers in 19 locations across six continents. Scientists from IBM Research have produced six Nobel Laureates, 10 U.S. National Medals of Technology, five U.S. National Medals of Science, six Turing Awards, 19 inductees in the National Academy of Sciences and 20 inductees into the U.S. National Inventors Hall of Fame

IBM has European research locations in Switzerland (Zurich), England (Hursley and Daresbury), and Ireland (Dublin), with a large development lab in Germany focused on AI, quantum computing, security and hybrid cloud.

IBM’s global labs are involved hundreds of joint projects with universities particularly throughout Europe, in research programs established by the European Union and the local governments, and in cooperation agreements with research institutes of industrial partners.

Compass is a 4-year PhD training programme focusing on Computational Statistics and Data Science. This new venture is part of the Compass mission to promote academic and professional agility in its students, equipping them with the skills and experience to work across disciplines in academia and beyond.

Anthony Stephenson is the PhD student recruited to this project says, “After several years working in industry, I am pleased to be starting the Compass programme and shifting my focus to research. Having the combined forces of the University of Bristol and IBM behind me inspires confidence and I look forward to working with members of each of them. My project, scalable inference in non-linear Bayesian models, is also a highly relevant and exciting area to work on, with many applications in modern machine learning.”

Dr Ed Pyzer-Knapp is World-Wide IBM Research Lead in AI Enriched Modelling and Simulation and says, “I am very excited to work with Anthony and Robert – scaling Bayesian inference is a really important area of machine learning research; bringing to bear our mantra of fusing of bits and neurons to further develop the future of computing. This project is a great opportunity to further strengthen our relationship with the University of Bristol.”

Prof Robert Allison is Anthony’s academic supervisor at the University of Bristol and says, “I’m really looking forward to working with Anthony and Ed on a highly important and widely applicable area of machine learning which encompasses mathematical research, data-analysis, algorithm development and efficient large-scale computation. In addition, I see this project as an ideal opportunity to seed wider ranging data-science and machine learning collaborations between IBM Research, their academic partners and the University of Bristol.”

As Director of Compass, Prof Nick Whiteley say “I’m absolutely delighted to welcome IBM Research to Compass. This project is a fantastic opportunity for Anthony to tackle a very challenging and increasingly important AI research problem under Prof. Allison and Dr. Pyzer-Knapp’s supervision. As this collaboration develops, I look forward to all Compass students learning about IBM’s vision for the future of AI and its connection to the expertise in statistical methodology and computing they will acquire through the Compass training programme.”

Improbable sponsors Compass PhD student in new partnership

Improbable, a global technology company which provides innovative products and services to makers of virtual worlds and simulations, is sponsoring a PhD research project entitled Agent-based model calibration using likelihood-free inference.

The University of Bristol is announcing a new industrial sponsor of Compass – the EPSRC Centre for Doctoral Training in Computational Statistics and Data Science. Improbable, a global technology company which provides innovative products and services to makers of virtual worlds and simulations, is sponsoring a PhD research project entitled Agent-based model calibration using likelihood-free inference. The project’s aim is to devise a general framework for calibrating agent-based models from training data by inferring the model parameters in a statistical framework.


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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