PhD position in Computational Science with focus on Mathematical Statistics – Theory and methods for data-driven decision support with applications in Swedish ambulance care with special focus on gender. - Befattningen är under tillsättning eller redan tillsatt, och det är inte längre möjligt att lämna in en ansökan

The Department of Mathematics and Mathematical Statistics is, together with Umeå Center for Gender Studies, searching for a PhD student in Computational Science with focus on Mathematical Statistics – Theory and methods for data-driven decision support with applications in Swedish ambulance care with special focus on gender. The employment will start on September 1, 2022, is limited to four years of full-time studies, and is based on the Department of Mathematics and Mathematical Statistics. Last day to apply is March 6, 2022.  

 The Department of Mathematics and Mathematical Statistics, Umeå University, performs research and doctoral studies in computational science, mathematics and mathematical statistics. The department has approximately 90 employees of which about 15 are PhD students. For more information about the department, see http://www.umu.se/en/department-of-mathematics-and-mathematical-statistics/ 

The Graduate School of gender studies has since 2001 co-financed PhD students at all of Umeå University’s faculties. A PhD student at the Graduate School of gender studies will take part in a unique and dynamic research environment, in which about 30 PhD students are participating in. For more information on the Graduate School of gender studies, see https://www.umu.se/en/umea-centre-for-gender-studies/doctoral-studies/the-graduate-school-of-gender-studies/  

Project description and tasks 
As a PhD student, you will work within an interdisciplinary project that aims to develop theories and methods for data-driven decision support with applications in Swedish ambulance care with a special focus on gender. Healthcare in Sweden must by law be equal, where equal care means, among other things, that care and treatment should be provided on equal terms to everyone regardless of gender, age, place of residence, functionality or sexual orientation, and regardless of combinations of these. A major challenge is how Sweden's regions, using the available data, can make organizational decisions that lead to healthcare being developed in a "desired" direction defined based on existing values and laws. 

Organizations have access to ever larger and more complex data, but how can we use statistical methods, including machine learning methods, to turn this data into good decisions? More specifically, the research project aims to answer the following key questions:  

• Based on a set of values – how do we weigh different interests together when making decisions?
• How do we make optimal decisions?
• What information is needed to make decisions?
• How do we use statistical methods to extract the necessary information from the available data? 

A common way to evaluate the ambulance service is to study the response times (the time the patient needs to wait for the ambulance). A change in ambulance care may mean that most residents get better ambulance care, but also that the difference between different patient groups increases. For example, that the differences between people living in urban and rural areas increases or that the gender differences increase. To optimize ambulance operations, we need to define a cost function and develop statistical methods that make it possible to develop relevant data-driven decision support.  

The doctoral project aims to develop new theory for data-driven decision support, develop a data-driven decision support for ambulance care, and to describe ambulance care in northern Sweden based on demographic and geographical parameters with a special focus on gender. The main supervisor of the project is Patrik Rydén, who is running an interdisciplinary research project with the goal of optimizing ambulance care in Sweden. The project has access to unique ambulance data and has several established contacts with the ambulance service in Sweden.  

Admission requirements 
Prerequisites include 240 ECTS credits (swe. Högskolepoäng) of higher education studies of which 60 ECTS credits should be on an advanced level (Master’s level).  

In addition to these general requirements, the applicant is required to have completed at least 90 ECTS credits in computational science courses, of which at least 30 credits shall have been acquired at the advanced level (Master’s level). Computational science courses refer to courses in statistics, mathematical statistics, computer science as well as relevant courses in biology, ecology, physics and chemistry. Applicants who in some other system either within Sweden or abroad have acquired largely equivalent skills are also eligible.  
 
Qualifications 
You have a degree of Master of Science in mathematical statistics, degree of Master of Science applied mathematics, Master of Science in engineering or an equivalent degree in a related field.  
 
We are looking for a driven person with a great interest in the research area, who is prepared to take on the challenges of the project that include both theory development in mathematical statistics and interdisciplinary applications.  

Good knowledge of statistics or mathematical statistics, programming (preferably MatLab, Python or R) and English is a requirement. Good knowledge of Swedish is a merit. Knowledge of gender studies and knowledge of gender research is a merit. 

You are expected to take an active role in the project, which includes having interdisciplinary collaborations with researchers from non-mathematical disciplines and external collaborations with ambulance staff from Sweden's regions. You should therefore be solution-oriented, flexible, structured and be good at communicating and collaborating.  

The assessments of the applicants are based on their qualifications and their ability to benefit from the doctoral-level education they will receive. 
 
Applicants with a degree not from a Swedish university are encouraged to provide results obtained from GMAT (and/or GRE) and TOEFL/IELTS tests if available. 

About the employment 
The position is intended to result in a doctoral degree and the main task of the PhD student is to pursue their doctoral studies which include both participation in research and postgraduate courses. The duties can include teaching and other departmental work (up to a maximum of 20%). The employment is limited to four years of full-time (48 months) or up to five years for teaching part-time. Salary is set in accordance with the established salary ladder for PhD position. The employment starts in the spring of 2020 or according to agreement. 

Application
A complete application should contain the following documents: 

• a personal letter with a brief description of your qualifications and your research interests. Motivate why you are applying for the employment and describe how your qualifications and merits are relevant to the employment.
• a curriculum vitae.
• reinforced copies of diplomas or equivalent, including documentation of completed academic courses, grades obtained, and possibly. other certificates.
• copies of relevant work such as Master’s thesis or articles that you have authored or co-authored.
• contact information for at least two reference persons. 

The Department of Mathematics and Mathematical Statistics values ​​the qualities that an even gender distribution brings to the department, and therefore we particularly encourage female applicants. 
 
You apply via our e-recruitment system Varbi with dnr AN 2.2.1-188-22. Log in and apply via the button at the bottom of the page. The deadline for applications is 2020-03-06.

The procedure for recruitment for the position is in accordance with the Higher Education Ordinance (chapter 12, 2§) and the decision regarding the position cannot be appealed. 

Further information 
Further information is provided by Patrik Rydén on e-mail patrik.ryden@umu.se or phone +46 907869562. 

We look forward to receiving your application!