Competitive Salary, Bonus & Benefits
Are you passionate about artificial intelligence (AI) and machine learning? Would you like to use your expertise to develop the next generation of drugs, and ensure their safety for patients? This is an opportunity to revolutionise the way that safety assessment is performed.
AstraZeneca is a global, science-led, patient-centred biopharmaceutical company that focuses on the discovery, development and commercialization of prescription medicines for some of the world’s most serious disease. But we’re more than a global leading pharmaceutical company. At AstraZeneca, we’re dedicated to being a Great Place to Work where you are empowered to push the boundaries of science and fuel your entrepreneurial spirit. There’s no better place to make a difference to medicine, patients and society.
About the Postdoc Programme:
Bring your expertise, apply your knowledge, follow the science and make a difference.
AstraZeneca’s Postdoc Programme is for self-motivated individuals looking to tackle exciting, high impact projects in a collaborative, engaging and innovative environment. You’ll work with peers and professionals from a diverse group of backgrounds, and a world class academic mentor specifically aligned to your project. We’ll help you develop valuable networks which support your research and future career development!
AstraZeneca Postdocs are respected as specialists and encouraged to speak up. They lead ground-breaking drug discovery and development research projects. Our vibrant, multi-disciplinary scientific teams empower and support our Postdocs, and we encourage them to share their research at conferences, publish papers, achieve their goals and make a difference to our patients.
You’ll learn from industry leaders working on innovative research across our organization. Our Postdoc Training Programme will support you to develop transferrable skills from influencing others to shape the agenda, to data analysis.
Are you ready to explore this exciting next step in your research career?
About the Opportunity:
Our in-house developed bone marrow microphysiological system (BM-MPS) is a dynamic model, comprised of haematopoietic stem cells that are maintained with simultaneous differentiation into myeloid, erythroid and megakaryocyte lineages. This enables drug-induced toxicity and post-drug recovery to be monitored in real-time by repeat sampling and analysis by multi-colour flow cytometry (MFC). The BM-MPS can address the clinical challenge of identifying combination/scheduling-induced BM toxicity, which is a significant dose-limiting side-effect for oncology drugs, and prevention often requires oncology drug dose-reduction or cessation in the clinic, limiting efficacy and thereby patient benefit.
While the BM-MPS has demonstrated clinical predictivity, current analysis methods do not take full advantage of these real-time data, thus we want to build an AI-based approach that is specifically applicable to these data. A key technique we would like to investigate is the Poincaré map. The map has been shown to outperform existing techniques at identifying hierarchies and branching processes, and can model continuous trajectories (Klimovskaia et al., 2020), thereby lending themselves to haematopoietic differentiation data. Other dimensionality reduction techniques, such as Palantir, PHATE and UMAP, could also be explored (Setty et al., 2019, Moon et al., 2020 and McInnes et al., 2020). Our hypothesis is that AI analysis will deliver mechanistic insight and enable alignment of haematotoxicity to a specific point in the differentiation process, enhancing predictions of toxicity and recovery responses, and ultimately improving design of combination-schedules.
Embedded in a collaborative team of biologists, technology experts and data scientists, and supported by a cross-discipline team, you will establish a new framework for haemtox. You’ll expand your knowledge of the bone marrow and haematopoeisis and develop your data science skills. Where appropriate, you will use our compute cluster to perform analysis. You’ll learn from experts across our organisation and gain exposure to drug projects spanning our therapy areas. We’ll support you to publish the methodology and application in high impact journals, and share your findings by giving national and international conference presentations.
Qualification, Skills & Experience
A PhD (or equivalent) in a numerate discipline
Proficient in Python or R (or similar programming language)
Experience with analysis of large data sets using advanced statistical or AI/machine learning techniques
The ability to inform and inspire audiences with a broad range of backgrounds and technical knowledge.
Ability to see opportunities, learn, and apply that learning to drive innovation
Good networking, collaboration and teamworking skills
Strong project management skills, with the ability to handle multiple projects in a fast-paced environment.
Experience with ‘omic data analysis, such as scRNA-seq and flow cytometry analysis
Experience with trajectory analysis and pseudotime methodologies
Experience with bone marrow and/or haematopoiesis
Use of a computer cluster (e.g. slurm workload manager)
Track record of high quality peer-reviewed publications
This is a 3-year programme. 2 years will be a Fixed Term Contract, with a 1-year extension which will be merit based.
Ready for an exciting, rewarding challenge? Apply today!
Advert Opens: 26th October, 2021
Advert Closes: 5th December, 2021
If you require any reasonable adjustments or accommodations during your application or interview process, please let us know.
- Salary £33000 - £43000
- Salary Per annum