Umeå University, Faculty of Science and Technology

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. And 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 what it is all about. But also about delivering education to enable regions to expand quickly and sustainably. This is simply where the future is built.

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The Department of Mathematics and Mathematical Statistics conducts research in computational mathematics, discrete mathematics, mathematical modelling and analysis, and mathematical statistics. Our teaching is conducted at all levels and includes mathematics, mathematical statistics and computational science. Among our partners are international research groups, academic institutions, public organizations and companies.

The Department of Mathematics and Mathematical Statistics is opening a PhD position in mathematical statistics, focusing on nonparametric regression modelling. The position covers four years of third-cycle studies, including participation in research and third-cycle courses. The last day to apply is May 14, 2023.

Project description and tasks 
What are the effects of climate change on the diversity of land birds? How many fur seals remain in Antarctica after breeding season? Do flies transmit the ‘bee’ parasite on flowers during defecation? Statistics is there to answer these big-scale and small-scale questions and to understand the world around us, each other and ourselves. When analyzing the relationships between a response and predictors, it might be natural to assume that some relationships obey certain shape constraints, such as monotonicity and convexity. 

Shape-constrained generalized additive models (SCAM) provide a general and powerful framework for nonparametric regression modelling with shape constraints, demonstrating their efficacy and practicality in numerous applications. The popularity of SCAMs lies in the attractive balance between applicability and interpretability. However, existing methods do not support models with large data sets, yet these are increasingly invaluable and important as technological advances across science and industry generate vast quantities of data. Moreover, efficient and robust computation is currently possible in the standard exponential family setting. 

The project aims to address these limitations by i) developing methods for fitting SCAM that can handle much larger data sets and more complex model structures than up to now been possible; ii) developing methods for models with response distribution beyond the standard cases; iii) developing open-source software that implements the new methods and meets the needs of scientific and industrial users within the relevant fields.

The project is partially funded by the Swedish Research Council.

The doctoral student will be admitted for studies at third-cycle level in Mathematical Statistics. To fulfil the general entry requirements, the applicant must have qualifications equivalent to a completed degree at second-cycle level or completed course requirements of at least 240 ECTS credits, including at least 60 ECTS credits at second-cycle level. 

To fulfil the specific entry requirements to be admitted for studies at third-cycle level in mathematical statistics, the applicant is required to have completed at least 60 ECTS credits within the fields of mathematical statistics, statistics and mathematics, of which at least 15 ECTS credits shall have been acquired at second-cycle level. Applicants who, in some other system either within Sweden or abroad, have acquired largely equivalent skills are also eligible. 

Good skills in R programming are required. Good communication skills in both written and spoken English is also a requirement. Documented knowledge and experience in regression modelling, generalized linear models, generalized additive models, mixed modelling, and computational statistics are merits. 

You are expected to participate in this project and institutional work actively. You have a scientific mindset, can work independently, and are structured, flexible and solution-oriented. Above all, you are determined to continuously develop your skills and contribute to nonparametric regression modelling research.

The assessment of applicants is based on their qualifications and ability to benefit from the doctoral study they will receive. 

About the employment 
The position is intended to result in a doctoral degree. The main task of doctoral students is to pursue their third-cycle studies, including active participation in research and third-cycle courses. The duties may include teaching or other departmental work, although duties of this kind may not comprise more than 20 percent of a full-time post. The employment is for a fixed term of four years full-time or up to five years when teaching part-time. Salary is set according to the salary ladder for PhD positions at Umeå University. Employment commences in the autumn of 2023 or by agreement.  

Applications will be accepted via our recruitment system. The deadline for applications is May 14, 2023. Log in and apply via the button at the bottom of the page. The application must include the following documents written in English or Swedish:

  • A cover letter briefly describing your qualifications and research interests, an explanation of why you are applying for the position, and why you feel your qualifications and experience are relevant.
  • Curriculum vitae.
  • Authenticated copies of degree certificates, diplomas, or equivalent, including documentation of completed academic courses, received grades, and other certificates.
  • Copies of relevant work such as master’s thesis or articles you have authored or co-authored. If the master’s thesis has not been completed before the application deadline, a summary of the master’s thesis project and current progress shall be included. The summary can, at most, be five pages, including figures and references.
  • Your GMAT (or GRE) and TOEFL/IELTS test scores, if available.
  • Contact details for at least two references. 

The Department of Mathematics and Mathematical Statistics values the qualities that gender balance brings to the department. We are therefore particularly keen to hear from female applicants. 

Pursuant to Chapter 12 Section 2 of the Swedish Higher Education Ordinance (SFS 1993:100), the decision regarding the position cannot be appealed. 

Additional information 
Further information can be provided by Associate professor Natalya Pya Arnqvist or Professor Jun Yu, You can also contact the head of the department, Professor Åke Brännström,, for additional questions.

Information about the Department of Mathematics and Mathematical Statistics:

Information about getting established in Umeå:

Type of employment Temporary position
Employment expires 2024-08-31
Contract type Full time
First day of employment Hösten 2023 eller enligt överenskommelse
Salary Månadslön
Number of positions 1
Full-time equivalent 100%
City Umeå
County Västerbottens län
Country Sweden
Reference number AN 2.2.1-516-23
  • Natalya Pya Arnqvist, Associate Professor,
  • Jun Yu, Professor,
Union representative
  • SACO, +46907865365
  • SEKO, +46907865296
  • ST, +46907865431
Published 23.Mar.2023
Last application date 14.May.2023 11:59 PM CEST

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