Postdoctoral FellowMulti-omics integration for disease likelihood inference with AI / Deep LearningCambridge, UKCompetitive Salary, Bonus & BenefitsAstraZeneca's Centre for Genomics Research (CGR) is looking for a highly motivated and creative Postdoc to work on an exciting project involving data mining on more than 500K whole genomes (WGS) and other omics datasets from UK Biobank and developing novel machine learning algorithms to translate obtained knowledge into clinical practice.
About AstraZenecaAstraZeneca is a global, science-led, patient-centred biopharmaceutical company focusing on discovering, developing, and commercialising prescription medicines for some of the world's most serious diseases. But we're more than a global leading pharmaceutical company. At AstraZeneca, we're dedicated to being a Great Place to Work and empowering employees to push the boundaries of science and fuel their entrepreneurial spirit. There's no better place to make a difference in medicine, patients, and society.
About the AZ Postdoc ProgrammeBring your expertise, apply your knowledge, follow the science, and make a difference. AstraZeneca's Postdoc Programme is for self-motivated individuals looking to deliver exciting, high-impact projects in a collaborative, engaging and innovative environment. You'll work with multidisciplinary scientific teams from a diverse set of backgrounds and a world-class academic mentor specifically aligned to your project. Our postdocs are respected as specialists, encouraged to speak up, and supported to share their research at conferences, publish papers, achieve their goals and make a difference to our patients.
This is a 3-year programme (Fixed Term Contract).About the OpportunityFuelled by next-generation sequencing, human genetics research has provided unprecedented insights into revealing mechanisms of many genetic diseases and brought great value to drug development. The CGR is an AstraZeneca initiative involving the generation and analysis of genetic data in participants from AstraZeneca clinical studies and large population cohorts including the 500K-participant UK Biobank study. Our in-house clinical genomic database is among one of the largest globally. These enable AstraZeneca to identify genetic determinants of disease risk, validate new targets for medicines, and improve patient stratification opportunities among the core areas of oncology, respiratory, immunology, cardiovascular, renal and metabolic disease.
An exciting Postdoctoral opportunity now exists in CGR, which involves analysing large-scale genomics (WES, WGS) and other omics (proteomics, metabolomics) data to infer complex biological insights from multi-faceted datasets and aid with clinical application. You will develop and apply advanced machine learning, deep learning and analytic methods to explore data patterns in multi-omics and other types of data. The goal for this postdoc opportunity is to achieve a deeper understanding of the non-coding genome and its contribution to disease, including the development of comprehensive genome-wide scores for disease likelihood prediction and using raw genomic sequences for disease inference.
You will become a member of CGR and work closely with a team of senior data scientists, machine learning engineers and genome analysts, having access to unprecedented datasets, including the UK Biobank project. We encourage you to conduct independent research and produce high-quality peer-reviewed publications and presentations at international meetings.
You will be supervised by Dr Dimitrios Vitsios (Director of Data Science and Genomics) and Dr Slavé Petrovski (VP & Head of Genome Analytics & Informatics) from CGR and co-supervised by an external academic advisor from the University of Cambridge.
Why Should You Apply- A unique opportunity to investigate unprecedented multi-omics datasets
- Gain experience of life science problems and conduct research in an interdisciplinary team
- Be part of a group of encouraging and ambitious data science and computational biology researchers at AZ
- Opportunity to collaborate with world-class researchers at the University of Cambridge
- Lead the project with the support of AZ supervisors and Academic experts
- Publish first-authored paper in high-impact journals
- Make contribution to address the unmet needs of patients
Essential Requirements- PhD in human genetics, statistical genetics, bioinformatics, machine learning, or other relevant subject area
- Experience with application of advanced analytics, including machine learning, in genomics
- Strong experience in programming, including Python or R, and in using high performance computing clusters
- Knowledge of genomics community algorithms and solutions. Strong interest in the potential of genomics to impact drug discovery
- Excellent communication skills, including writing of manuscripts and oral presentations
- Highly motivated, well-organised and resourceful
- Able to work well both as part of a team and independently.
Why AstraZeneca?At AstraZeneca we're dedicated to being a Great Place to Work. Where you are empowered to push the boundaries of science and unleash your entrepreneurial spirit. There's no better place to make a difference to medicine, patients and society. An inclusive culture that champions diversity and collaboration. Always committed to lifelong learning, growth and development.
This role is open from 8th March, and we encourage your application by 15th March.Apply now!Further information can be found here:Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/
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Date Posted08-Mar-2023
Closing Date15-Mar-2023
AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.