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英国剑桥贝叶斯机器学习博士后职位

2018年03月26日
来源:知识人网
摘要:

Postdoctoral Long Title:

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. Yo u'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.

 

About AstraZeneca

AstraZeneca is a global, innovation-driven biopharmaceutical business that focuses on the discovery, development and commercialisation of prescription medicines for some of the world's most serious diseases. But we're more than one of the world's leading pharmaceutical companies. At AstraZeneca, we're proud to have a unique workplace culture that inspires innovation and collaboration. Here, employees are empowered to express diverse perspectives – and are made to feel valued, energised and rewarded for their ideas and creativity.

 

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