Thesis work: Bayesian sample size calculation

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!

Bayesian sample size calculation for the coefficient of variation
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 sample size calculation to determine the minimum sample size required to detect differences on the coefficient of variation for samples analysed at different time points with a certain level of confidence. We aim to reduce the number of animals used with this approach.

Background
A common requirement in biological experiments is to analyse samples within a certain time after collection. This can be difficult or impossible due to practical considerations, leading to a delay in sample analysis. Comparing the effect of analysing samples at different time points can be done using the coefficient of variation and a number of approaches has been discussed in literature; see for example Banik et. al (2012) and Shoukri et. al (2008).  In this thesis, we are interested in applying the Bayesian bootstrap (Rubin, 1981) to do a sample size calculation where the parameter of interest is the coefficient of variation.

At times not all paired observations are available due to various reasons such as blood clot or aspiration failure in haematology studies. There are various methods to handle data with missing observations such as complete case analysis and imputation. One approach, proposed by Samawi and Vogel (2014), splits the data into two set (one set for complete paired observations and the second set for incomplete paired observation) and applies weights. The thesis will explore this idea in the Bayesian context.  This will involve Monte-Carlos simulations and actual experimental data.

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.