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- Tasks: Join us to develop Bayesian machine learning models predicting drug toxicity in various organs.
- Company: AstraZeneca is a leading global pharmaceutical company based in Cambridge, UK.
- Benefits: Enjoy a competitive salary, comprehensive training, and support from top academic advisors.
- Why this job: Be part of innovative projects, collaborate with experts, and contribute to impactful research.
- Qualifications: PhD in Statistics, Computer Science, or related field; strong skills in R or Python required.
- Other info: This is a 3-year programme with opportunities for independent research and conference presentations.
The predicted salary is between 36000 - 60000 £ per year.
Postdoc in Bayesian machine learning, AstraZeneca, Cambridge, UK
Mar 29, 2018
PREDICTING DRUG TOXICITY WITH BAYESIAN MACHINE LEARNING MODELS
We’re currently looking for talented scientists to join our innovative academic-style Postdoc. From our centre in Cambridge, UK you’ll be in a global pharmaceutical environment, contributing to live projects right from the start. You’ll take part in a comprehensive training programme, including a focus on drug discovery and development, given access to our existing Postdoctoral research, and encouraged to pursue your own independent research. It’s a newly expanding programme spanning a range of therapeutic areas across a wide range of disciplines. What’s more, you’ll have the support of a leading academic advisor, who’ll provide you with the guidance and knowledge you need to develop your career.
You will be part of the Quantitative Biology group and develop comprehensive Bayesian machine learning models for predicting drug toxicity in liver, heart, and other organs. This includes predicting the mechanism as well as the probability of toxicity by incorporating scientific knowledge into the prediction problem, such as known causal relationships and known toxicity mechanisms. Bayesian models will be used to account for uncertainty in the inputs and propagate this uncertainty into the predictions. In addition, you will promote the use of Bayesian methods across safety pharmacology and biology more generally. You are also expected to present your findings at key conferences and in leading publications
This project is in collaboration with Prof. Andrew Gelman at Columbia University, and Dr Stanley Lazic at AstraZeneca.
Education and Experience Required:
– PhD in Statistics, Computer Science, Data Science, or similar
– Excellent knowledge of either R or Python (ideally both)
– Knowledge of Bayesian statistics
– Knowledge of modern Bayesian software such as Stan and PyMC3
– Knowledge of (or an interest in) life sciences
This is a 3 year programme. 2 years will be a Fixed Term Contract, with a 1 year extension which will be merit based. The role will be based at Cambridge, UK with a competitive salary on offer.
To apply for this position, please follow the link below:
https://job-search.astrazeneca.com/job/cambridge/post-doc-fellow-bayesian-machine-learning/7684/7417160
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Postdoc in Bayesian machine learning, AstraZeneca, Cambridge, UK employer: The International Society for Bayesian Analysis
Contact Detail:
The International Society for Bayesian Analysis Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Postdoc in Bayesian machine learning, AstraZeneca, Cambridge, UK
✨Tip Number 1
Network with professionals in the field of Bayesian machine learning and drug discovery. Attend relevant conferences or seminars where you can meet researchers from AstraZeneca or similar organisations, as personal connections can often lead to job opportunities.
✨Tip Number 2
Familiarise yourself with the latest advancements in Bayesian statistics and machine learning. Being well-versed in current research and methodologies will not only enhance your knowledge but also demonstrate your commitment and expertise during interviews.
✨Tip Number 3
Engage with online communities and forums focused on Bayesian methods and machine learning. Participating in discussions or contributing to projects can help you build a reputation in the field and may catch the attention of recruiters.
✨Tip Number 4
Prepare to discuss your independent research ideas that align with AstraZeneca's focus areas. Showing initiative and a clear vision for your contributions can set you apart from other candidates and highlight your potential value to the team.
We think you need these skills to ace Postdoc in Bayesian machine learning, AstraZeneca, Cambridge, UK
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your PhD in Statistics, Computer Science, or Data Science. Emphasise your experience with Bayesian statistics and any relevant projects that showcase your skills in R or Python.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and AstraZeneca's mission. Discuss how your background aligns with the requirements, particularly your knowledge of Bayesian methods and life sciences.
Showcase Relevant Experience: Include specific examples of your work with Bayesian machine learning models, especially any projects related to drug toxicity or safety pharmacology. This will demonstrate your capability and fit for the position.
Prepare for Interviews: If selected for an interview, be ready to discuss your research in detail. Prepare to explain your understanding of Bayesian statistics and how you would apply it to predicting drug toxicity, as well as your interest in collaborating with leading academics.
How to prepare for a job interview at The International Society for Bayesian Analysis
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in R and Python during the interview. Be prepared to discuss specific projects where you've applied Bayesian statistics and any modern Bayesian software like Stan or PyMC3.
✨Demonstrate Your Knowledge of Drug Discovery
Familiarise yourself with the drug discovery process and how Bayesian machine learning can be applied to predict drug toxicity. This will show your understanding of the role and its relevance in a pharmaceutical context.
✨Prepare for Collaborative Discussion
Since this position involves collaboration with leading academics, be ready to discuss how you work in teams. Share examples of past collaborations and how you’ve contributed to joint research efforts.
✨Express Your Research Interests
Articulate your independent research interests and how they align with the goals of AstraZeneca. This shows initiative and a desire to contribute to the field beyond just the assigned projects.
