Project description
The project will focus on large population cohorts of patients with type 2 diabetes, with comprehensive genomic data and longitudinal medical records. The aim is to investigate variation in response to existing diabetes medication and use statistical/machine-learning approaches to identify biological predictors of response. The student will become proficient in data science, genomics, and machine learning approaches applied to health data. As such, we expect successful candidates to have an interest and experience in at least one of the core threads of the project:
a) statistical analyses of longitudinal/timecourse data;
b) machine learning approaches for integrating heterogenous data;
c) analysis of genomic (including functional genomic) data;
d) analysis of EHR or real world evidence clinical data
A single medication rarely shows equal efficacy across heterogenous patient groups. Most Type-2 Diabetes patients progress in their disease and consequently in their medication profiles. Progression of disease results in a sub-optimal match in medication as well as increasing risk of complications. Genetic predisposition in patients as well as patient and disease characteristics plays a role in disease predisposition and progression as well as response to medication and pharmacokinetics.
Machine learning/AI provides the ability to draw on the complex signals from genetics, patient behavior/compliance, drug dosing, longitudinal response and patient characteristics. An artificial intelligence-based predictor can integrate patient contextual information with genetics and disease information to discriminate responders from poor responders at early stages. A successful predictor of response can be reverse engineered to identify features that drive prediction, and thereby identify genetics that contributes to such models. These genetic drivers can then be translated into disease genes of interest and potential drug targets in the cardiometabolic space.
The position is hosted at the University of Dundee. As the project has cross-functional aims, co-localisation across Dundee and Oxford is expected, with some flexibility to the personal situation of the candidate.
About the School of Medicine, University of Dundee
The School of Medicine is based on the University of Dundee’s Ninewells campus, co-located with Ninewells hospital (one of the largest teaching hospitals in the UK). The medical school has been ranked 1st in the UK for Medicine – in both the Guardian’s University Guide, 2021 and the Complete University Guide, 2021. The calibre of research at Dundee is high. The School of Medicine was rated first in the UK for the impact of its research in REF2014, with 95% of staff working in areas of national or international excellence.
Health informatics and Precision Medicine are major themes of clinical research in Dundee, targeted at using ‘big data’ to improve the health of individuals and society. Significant internal investment was made in 2012-3 to enhance the Health Informatics Centre capacity and this has been associated with major external funding for the Farr Institute, which was led jointly by the University of Dundee and partners; and more recently the Health Data Research-UK institute, of which Dundee is part of the Scottish substantive site. The University of Dundee was named as the world’s most influential pharmaceuticals research institution in the State of Innovation report by Clarivate Analytics, for the period 2006-2016, ranking above MIT.
We pride ourselves on delivering an excellent research-led teaching and learning experience for undergraduate and postgraduate students in Medicine, Dentistry and Biomedical Science. We have a vibrant programme for undergraduate research projects (BSc (Hons) & intercalated BMSc), Masters by Research and PhD students and provide training for postdoctoral researchers supported by research awards and personal fellowships.
About Novo Nordisk & Novo Nordisk Research Centre Oxford (NNRCO)
Novo Nordisk is a leading global healthcare company, founded in 1923 and headquartered in Denmark. NNRCO is Novo Nordisk’s new Translational Research Unit (TRU) focused on biology and target discovery across the broad spectrum of cardiometabolic disease. Our mission is to be a world-leading research site focused on asking the big and difficult questions and delivering high impact science. We use genetics, functional genomics, human-centric disease models and computational biology to develop an unparalleled understanding of cardiometabolic disease and deliver therapies that transform the lives of patients.
The NNRCO Computational Biology Department, led by Director Ramneek Gupta, incorporates a diverse range of computational and big data experience, with a focus on target identification and providing insights from multiple streams of data. The department enjoys a diversity of skills and experience encompassing multi-omics data integration, machine learning, chemoproteomics approaches, genetics incorporation, bioinformatics tools, ontologies and databases. Collaborations from the department extend into the academic and commercial ecosystem, as well as internally across different parts of the organization.
Qualifications
You have a relevant background (MRes/MSc required) in computational biology or in a similar relevant discipline along with programming skills in python or R. Preferably you have some experience with scripting in a Unix environment, high performance compute environments and in machine learning. A background in human disease biology is an advantage, as is experience in working with real world clinical data. Candidates without hands-on experience in at least one of the core threads of the project, will not be pursued.
Personally, you are conscientious and contribute to a positive working environment as a part of a team. Your passion lies in deriving value from applying data science to orthogonal data streams and in elucidating the biology underlying complex diseases. Finally, you are excited about the opportunities available today with big data applications in solving biological and medical problems.
Start date - as soon as possible
Enquiries - Ewan Pearson, Head of Division, Population Health & Genomics, School of Medicine, University of Dundee +441382383387 [Email Address Removed]; Ramneek Gupta, Director, Computational Biology, Novo Nordisk Research Centre Oxford +447824606773 [Email Address Removed]
Apply - Please send a copy of your CV with covering letter to [Email Address Removed] by Monday 15 November 2021.
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