Umeå University, Faculty of Science and Technology

Umeå University is one of Sweden’s largest institutions of higher education with over 35,000 students and 4,200 faculty and staff. We are characterised by world-leading research in several scientific fields and a multitude of educations ranked highly in international comparison. Umeå University is also the site of the pioneering discovery of the CRISPR-Cas9 genetic scissors - a revolution in genetic engineering that has been awarded the Nobel Prize in Chemistry.

At Umeå University, everything is nearby. Our cohesive campus environment makes it easy to meet, collaborate and exchange knowledge, which promotes a dynamic and open culture where we rejoice in each other's successes.

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 at Umeå University is opening a PhD position in mathematical statistics, focused on the interplay between optimization and machine learning. The position is for four years of doctoral studies which include both participation in research and postgraduate courses. Last day to apply is June 15, 2021.

Project description and tasks
The interplay between optimization and machine learning is the cornerstone of many important advances in inference systems and artificial intelligence in the last decade. The vast majority of machine learning applications are modeled and solved as an optimization problem. To accommodate the increasing complexity of problem models along with massive amounts of data, machine learning entails the development of new optimization methods. In contrast to the traditional black-box optimization framework, an end-to-end view of modeling and optimization is central to these novel algorithms.

Broadly speaking, the objective of this doctoral project is to develop new principles and algorithms to expand the practical and theoretical frontiers of optimization and machine learning. This project explores stochastic approximation and randomized linear algebra to introduce new methods effective for high dimensional problems, and to potentially explore their applications in statistical learning, deep neural networks, and reinforcement learning.

The project is part of the AI/MLX track of the Wallenberg AI, Autonomous Systems, and Software Program (WASP) and the PhD student will be enrolled in the WASP graduate school, see https://wasp-sweden.org/graduate-school/ for more information.

Qualifications
The PhD student will be admitted to third-cycle studies in either mathematical statistics (MS) or computational science and engineering (CSE) with specialization in mathematical statistics.

General entry requirements 
To be admitted for studies at third-cycle level the applicant is required to have completed a second-cycle level degree, or completed course requirements of at least 240 ECTS credits, of which at least 60 ECTS credits are at second-cycle level, or have an equivalent education from abroad, or equivalent qualifications.

Specific entry requirements
For third-cycle studies in Mathematical Statistics, the applicant is required to have completed at least 60 ECTS credits within the field of mathematical statistics, statistics and mathematics, of which at least 15 ECTS credits shall have been acquired at second-cycle level. 

For third-cycle studies in CSE, the applicant is required to have completed at least 90 ECTS credits in CSE courses, of which at least 30 ECTS credits shall have been acquired at second-cycle level. CSE courses refer to courses with major quantitative, statistical or computing science elements, such as courses in computing science, mathematics and mathematical statistics.

Applicants who in some other system either within Sweden or abroad have acquired largely equivalent skills are also eligible.

Programming skills (preferably MatLab or Python) are required. Good knowledge of English language, both written and spoken, are key requirements. Documented knowledge and experience in optimization and machine learning are merit.

You are expected to play an active role in the development of this doctoral project and also in the department. You are expected to have a scientific and result-oriented approach for your work. You should therefore have a very good communication and collaboration ability. You are structured, flexible and solution-oriented.

The assessments of the applicants are based on their qualifications and their ability to benefit from the doctoral-level education they will receive.

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 participation in research and doctoral courses, and to take part in the WASP graduate school. The duties can include teaching and other departmental work (up to a maximum of 20%). The employment is limited to the equivalent of 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 levels for PhD position. The employment starts in the fall of 2021 or according to agreement.

Application
You apply via our e-recruitment system Varbi. Log in and apply via the button at the bottom of the page. The deadline for applications is June 15, 2021.

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,
  • authenticated copies of degree certificates 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.

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.

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.

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 Professor Jun Yu, +46 90 7865127, jun.yu@umu.se. You can also contact the head of department Åke Brännström for additional questions at ake.brannstrom@umu.se.

More information about the department: https://www.umu.se/en/department-of-mathematics-and-mathematical-statistics/

We look forward to receiving your application!

Type of employment Temporary position longer than 6 months
Contract type Full time
First day of employment Fall 2021 or according to agreement.
Salary Monthly salary
Number of positions 1
Working hours 100 %
City Umeå
County Västerbottens län
Country Sweden
Reference number AN 2.2.1-568-21
Contact
  • Jun Yu, professor, 090-7865127, jun.yu@umu.se
  • Åke Brännström, head of department, 090-7867862. ake.brannstrom@umu.se
Union representative
  • SACO, 090-786 53 65
  • SEKO, 090-786 52 96
  • ST, 090-786 54 31
Published 13.Apr.2021
Last application date 15.Jun.2021 11:59 PM CET

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