Thesis work: A Bayesian analysis workflow

Job description
Do you enjoy applying statistics and mathematics to biological problems? Would you like to help develop life changing medicines? Then AstraZeneca might be of interest to you!

A Bayesian analysis workflow for pre-clinical experiments
Thesis work: 30 credits

At AstraZeneca, we turn ideas into life changing medicines and strive to continuously meet the unmet needs of patients worldwide. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality. If you are swift to action, confident to lead, willing to collaborate, and curious about what science can do, then you’re our kind of person.

Responsibilities
As an MSc student in the Quantitative Biology group in Gothenburg, you will be part of a large team of statisticians and bioinformaticians and will have the opportunity to collaborate with colleagues across sites in Sweden, the UK and the USA. You will improve both your programming and statistical skills to tackle challenges in our drug development pipeline. The focus will be on developing a flexible workflow to detect trends and anomalies amongst studies, and to explore and evaluate the effect of different prior distributions on the Bayes factor. We aim to reduce the number of animals used in future experiments.

Background
Sample size calculations are carried out before conducting an experiment to determine the minimum sample size required to detect an effect of a given size with a certain level of confidence. Determining an effect size can be challenging at times. The Bayesian approach uses prior knowledge on the distribution of the effect as opposed to a single value in the frequentist setting. Other than the effect size, the distribution of the data in different groups in a study can be deduced from previous similar studies. Thus the prior knowledge of each treatment group including the vehicle group will be used to inform future studies.  This enables us to evaluate the uncertainty of the parameters. 

After the experiment has been conducted, biologists are often interested to determine if a new compound lead to an improvement compared to existing drugs. The use of the p-values to reject or fail to reject a null hypothesis is common. As an alternative the Bayes factor (Kass and Raftery, 1995) is used to measure the weight of the evidence of one hypothesis, say, alternative, over the null hypothesis. Thus, rather than reject or fail to reject a null hypothesis, the Bayes factor provides weight of the evidence as given by data. Interpretation of Bayes factor is also provided in literature see Jeffreys (1961) and Raftery (1995).

Qualifications
Essential Requirements
• Competence in mathematics
• Basic programming (R, Stan, python or similar) and statistical skills
• Enjoy working as part of a team at AstraZeneca’s site in Gothenburg

Desirable Requirements
• A basic understanding of biology would be a great asset

Application
Randstad Life Sciences is cooperating with AstraZeneca in this recruitment process. We only accept applications through Randstad’s website.

Deadline for application: 2020-03-31, selection and interviews will be ongoing. The position may be filled before the last day of application, therefore, apply as soon as possible.

For more information: Kerstin Karlsson kerstin.karlsson@randstad.se or Eleonor Ehrman +4673-343 41 09.

About the company
Our Gothenburg site is one of AstraZeneca's three strategic science centers. We thrive in a multinational environment working cross-functionally across the globe with AstraZeneca colleagues as well as academic and industry partners. Our way of life is to foster a working environment that nurtures, collaboration, openness and innovation. Therefore, we have created space for meetings, socializing and relaxation, where spontaneous meetings can give birth to new innovations. The unexpected ideas or thoughts that can come from a chat over something as simple as a cup of coffee or a stroll on our “walk and talk” meeting trail.

AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, sex or sexual orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law. AstraZeneca only employs individuals with the right to work in the country/ies where the role is advertised