Umeå University is one of Sweden’s largest higher education institutions with over 37,000 students and about 4,700 employees. The University offers a diversity of high-quality education and world-leading research in several fields. Notably, the groundbreaking discovery of the CRISPR-Cas9 gene-editing tool, which was awarded the Nobel Prize in Chemistry, was made here. At Umeå University, everything is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture.
The ongoing societal transformation and large green investments in northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here.
The department of Statistics at Umeå School of Business, Economics and Statistics, is looking for a postdoc in Statistics, who can perform high quality methodological statistical research within the area of causal inference and machine learning. Apply 2024-08-25 at the latest.
The department of Statistics has about 30 members of staff and conducts research within the field of statistics and data science, including both method development and empirical research, the latter in collaboration with scientists from other departments. We offer a research environment with access to national and international networks. Our research profile focuses on development of novel statistical methods and software for the analysis of large and complex data sets. Applications include evaluation of labor market measures, health and quality of health care, as well as large-scale achievement tests. For more information: https://umu.se/en/usbe/about-us/statistics/.
Work description The successful candidate is expected to plan and perform independent research, but also to work in close collaboration with other researchers at the department as well as with researchers from other disciplines. The research will be performed within the externally funded project "Machine learning to study causality with big datasets: towards methods yielding valid statistical conclusions". The position may also, by agreement, include teaching at undergraduate and graduate levels in statistics up to 20% of full time.
The position is for two years, with starting date December 1, 2024, or upon agreement.
Requirements and qualifications Applicants should have a PhD in statistics/ mathematical statistics/ data science (or related area) before starting the position. Priority will be given to candidates who have completed their doctoral degree no more than three years before the closing date of the application. A candidate who has completed their degree prior to this may be considered if special circumstances exist. Special circumstances include absence due to illness, parental leave, appointments of trust in trade unions or similar circumstances.
The main assessment criteria for the appointment are documented research skills. The applicant is expected to have documented experience of:
Developing novel theory and methods within the fields of causal and/or semi-parametric inference (including methods based on machine learning algorithms).
Ability to work independently as well as part of a research group.
In addition, excellent programming skills in relevant languages, and excellent communication skills in written and spoken English are required. You must have good interpersonal skills and be able to work in a focused, flexible and proactive manner. Experience of interdisciplinary research projects and collaboration with scientists from other fields is qualifying.
How to apply The application should include:
A letter of application with a motivation describing your research interests (maximum of 2 pages).
A proposed research plan (maximum of 5 pages).
A Curriculum Vitae.
A publication list.
Copies of the PhD thesis and relevant publications.
Copies of relevant degree certificates and other documentation you wish to include in support of your application.
The names, with contact details and e-mail addresses, of at least two reference persons.
The application is to be submitted on the University recruitment system no later than 2024-08-25.
Information For further information please contact Professor Xavier de Luna, +46 (0)90 7865559, xavier.de.luna@umu.se.
More about Umeå School of Business, Economics and Statistics (USBE) As an internationally respected, nationally influential, and regionally rooted part of Umeå University, Umeå School of Business, Economics, and Statistics contributes to societal development through education and research of a high international standard.
Through interplay with surrounding society, we provide education and research that contributes to the understanding, ability, and responsibility of individuals in relation to societal challenges and the importance of sustainable development.
In collaboration with our surrounding society, we provide education and research that contributes to individuals' understanding, ability and responsibility in relation to societal challenges and the importance of sustainable development. We are AACSB-accredited and sustainability certified according to the environmental management standard ISO14001.
The Department of Business Administration, the Department of Economics, the Department of Statistics and The USBE office form USBE, with about 150 employees. About 3800 students follow our programs every year and we offer education from the undergraduate to the doctoral program level in all of our main disciplines – Business Administration, Economics and Statistics.
The Department of Statistics has about 30 members of staff. We conduct research with the field of Statistical Sciences, both method development and empirical research, in collaboration with other sciences.
Umeå University wants to offer an equal environment where open dialogue between people with different backgrounds and perspectives lay the foundation for learning, creativity and development. We welcome people with different backgrounds and experiences to apply for the current employment.
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