A fully funded PhD Studentship is available to work with Dr Anna Lobley, Associate Director, Biological Data Science at Exscientia, Dr Arkaitz Zubiaga, Senior Lecturer at the School of Electronic Engineering and Computer Science, Queen Mary University London, and Dr Claudia Cabrera, Lecturer in Bioinformatics at the William Harvey Research Institute at Queen Mary University London.
Awards will cover UK tuition fees, stipend at UKRI rate (currently £19,668), and a consumable allowance for 4 years (pro-rata for part-time applicants).
Applications will be reviewed on a rolling-basis up until the deadline of August 31st 2023. The studentship may be awarded prior to the August deadline and those interested in applying are encouraged to submit their application as soon as it's ready.
Project Description:
Methods for automated target and biomarker identification typically involve ranking genes and proteins according to indication relevance criteria. A typical process then involves traversing scientific literature for supporting evidence. However, many age-related western world diseases bear the hallmarks of complex heterogeneous conditions that vary along a spectrum of disease severity. They frequently involve multiple systems and pathways. Hence selection pools comprise many hundreds to thousands of genes. Selecting the best targets and stratification biomarkers from a large candidate pool presents a significant challenge in drug discovery. Current approaches are at best semi-automated or rely on expert opinion. This means it is difficult to avoid bias in such decision making tasks. Decision theory is one branch of Artificial Intelligence that can be applied to help resolve these complexities. Automated reasoning and argumentation theory are two appropriate branches of natural language processing well suited to the task. The aim of this project is to fully automate target and biomarker selections using a combination of NLP-based and recommendation methods. The end goal is to generate unbiased decisions from a complex network of information relationships.
We are seeking a highly motivated students who are passionate about contributing to biological knowledge through
the application of NLP to large text corpora and biomolecular data sets. The ideal candidates will have a background in data science, natural language processing or biomedical informatics/bioinformatics – this could be through a Masters degree in a subject, or alternately you may have a first class degree in computer science followed by bioscience experience, or vice versa. You will be confident in coding in Python, with some experience of natural language processing, machine learning, data wrangling and/or statistics.
Exscientia is an AI-driven pharmatech company committed to discovering, designing and developing the best possible drugs in the fastest and most effective manner. You will work closely with world-class scientists at Exscientia and will be based in the Biomarker and Targets Data Science Team, benefiting from their experience in AI and network systems biology methods applied to drug discovery.
This project is part of the UKRI/BBSRC AI for Drug Discovery Progamme, and successful candidates will join a cohort of students working on complementary projects in the AI for Drug Discovery space.
Eligibility and applying
We are looking for highly motivated individuals who are passionate about contributing to new discoveries in drug discovery bioscience through the application of the latest techniques in AI and data science. Ideal candidates will have a grounding in both a natural science and data science, e.g. through a Master's degree in a subject such as bioinformatics or computational chemistry. Alternatively, you may have, for example, a first-class degree in computer science followed by biochemistry experience, or vice versa (qualifications and evidence thereof must be obtained before 19/09/2023). You will be confident in performing data wrangling and analysis in a language such as Python, R or C++. Effective communication skills are essential.
Candidates must meet the UKRI requirements to be eligible for the award. Typically this means candidates have unrestricted access on how long they can remain in the UK (i.e. are a British National, have settled, or pre-settled status, have indefinite leave to remain etc.) and have been living in the UK for the 3 years immediately prior to studentship starting. This award is unfortunately not available to students who would be classed as international.
Applications will be reviewed on a rolling-basis up until the deadline of August 31st 2023. The studentship may be awarded prior to the August deadline and those interested in applying are encouraged to submit their application as soon as it's ready.
The projects start in September 2023. For more details, including eligibility and how to apply, see https://www.qmul.ac.uk/deri/ukri-aidd-doctoral-training-programme/apply/
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