Postdoctoral Fellow – Understanding chronic obstructive pulmonary disease heterogeneity using multi-trait genetic

3 year fixed term contract

Cambridge Biomedical Campus, UK

Competitive salary and benefits

Do you have expertise in, and passion for statistical genetics, bioinformatics, and machine learning? Would you like to apply your knowledge to impact projects in a company that follows the science and turns ideas into life-changing medicines? Then join the Translational Science and early Clinical Development department at AstraZeneca and unlock the power of what science can do!

In this exciting Postdoctoral Fellow position, you’ll be investigating the genetics of chronic obstructive pulmonary disease heterogeneity and then translating these genetic insights into clinically informative tools.

This project is supported by the Translational Science and early Clinical Development department that works in the Respiratory therapy area with the aim of translating cutting edge science into the development of transformative therapies for patients.

By harnessing cutting-edge statistical genetics, machine learning, and multi-trait and multi-omics approaches, this project seeks to understand the mechanisms of COPD heterogeneity and develop methodologies for high-resolution polygenic risk scores for COPD. Through the characterisation of pleiotropic genetic influence across respiratory and multimorbid traits, we aim to identify the biological pathways and molecular mechanisms that drive variation in disease progression, treatment response, and patient outcomes.

These insights will be leveraged to define clinically meaningful COPD subtypes, improve prediction of disease trajectories, and support the development of precision medicine strategies for respiratory disease.

Supported by Glenda Lassi, Associate Principal Scientist at AstraZeneca, and Benjamin Georgi, Principal Scientist at AstraZeneca, you'll also receive academic mentorship and guidance from Jing Chen, Lecturer in Statistical Genetics within the Division of Public Health and Epidemiology, School of Medical Sciences at the University of Leicester.

Our Postdoctoral Fellow will conduct ground-breaking research to understand the biological mechanisms underlying COPD heterogeneity. Working at the interface of statistical genetics, machine learning, bioinformatics, and respiratory medicine, you will develop innovative approaches that leverage large-scale genomic, clinical, and multi-omics datasets to improve our understanding and prediction of COPD progression. You will be part of a collaborative research environment spanning AstraZeneca and the University of Leicester, with opportunities to publish impactful research, engage with multidisciplinary teams, and contribute to the development of precision medicine strategies for respiratory disease.

• Use advanced bioinformatics, machine learning and statistical genetics methodologies to investigate COPD.
• Lead and drive the project under the supervision of cross-functional AstraZeneca team and in collaboration with the academic expert.
• Plan, write, publish, and present high-quality scientific papers.

• Strong background in statistical genetics and genomics, with experience in analysing GWAS summary statistics and developing polygenic risk scores (PRS).
• Expertise in deep learning and machine learning methodologies, including the development of predictive models.
• Proficiency in programming for data analysis and algorithm engineering, necessary for implementing models and developing user-friendly software packages.
• Experience working with large-scale human genetic datasets for model training,…