Uppsala University, Department of Information Technology

Are you interested in working with development of new algorithms for combinatorial optimization, with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? You are welcome to apply for a PhD student position at Uppsala University.

The Department of Information Technology holds a leading position in both research and education at all levels. We are currently Uppsala University's third largest department, with 350 employees, including 120 teachers and 120 PhD students. Approximately 5,000 undergraduate students take one or more courses at the department each year. You can find more information about us on the Department of Information Technology website.

Project description
Many problems in applied data- and computer science are naturally formulated as optimization problems. In this paradigm, we solve problems by first formulating a criterion that describes the qualities of a good solution. We then use various optimization methods to find a solution that is as good as possible according to our chosen criterion. The ubiquity of this approach to problem solving means that good optimization methods are a key enabling technology in many areas of computer science and its many applications.

In this project, we focus on a special class of combinatorial optimization problems, called lexicographic max-ordering (Lex-MO) optimization problems. Our interest in this class of problems is motivated by a recent discovery made by our team: Many optimization problems that are currently considered infeasible to solve in practical time (NP-hard) can be solved in low-order polynomial time if we recast them as Lex-MO problems! This includes many problems that naturally occur in practical applications.

The overall aim of this proposal is to provide a detailed and systematic characterization of the class of Lex-MO optimization problems that can be solved using efficient, low-order polynomial time, algorithms. This project aims to develop new algorithms, methods, and insights in combinatorial optimization with a high potential impact on many applied problems in data analysis and computer science.

The project is financed by a grant from the Swedish Research Council.

Duties
The doctoral student will primarily devote their time to graduate education. Other departmental duties of at most 20%, including teaching and administration, may also be included in the employment.

Requirements
General entry requirements for doctoral education are regulated in the Higher Education Ordinance. An applicant shall be considered as meeting the general entry requirements if they have:

  • completed a degree at the advanced level (Master’s level), or
  • completed course requirements of at least 240 credits, of which at least 60 credits are at the advanced level (Master’s level), or
  • acquired substantially equivalent knowledge in some other way in Sweden or abroad.

In order for a person who has completed course requirements of at least 240 credits (under the second item above) to be considered eligible at Uppsala University, the 60 credits at advanced level must include a degree project of at least 15 credits

The University may permit an exemption from the general entry requirements for an individual applicant, if there are special grounds (Chapter 7, § 39 of the Higher Education Ordinance). For special entry requirements, please see the subject’s general study plan.

Additional qualifications
We are are looking for candidates with:

  • a strong interest in developing new methods and algorithms for combinatorial optimization,
  • good communication skills with proficiency in oral and written English,
  • excellent study results,
  • high proficiency in programming (preferably in low level languages such as C/C++ or similar),
  • personal characteristics such as a high level of creativity, thoroughness, and/or a structured approach to problem-solving.

Experience and courses in one or more subjects are valued: optimization, graph theory, algorithms and data structures, complexity theory, computerized image analysis or computer vision.

Application
The application must include:

  • a statement (at most 2 pages) of your motivation for applying for a Ph.D. position at our department, including a self-assessment on why you would be the right candidate for this project,
  • a CV,
  • degrees and transcript of records with grades (translated to English or Swedish),
  • the Master’s thesis or equivalent document and, if applicable, other self-produced technical texts, publications, and other relevant documents,
  • references with contact information (names, emails and telephone numbers), but no letters of recommendation.

All applicants should state the earliest possible starting date of employment.

About the employment
The employment is a temporary position to four or five years, depending on the scope of teaching, according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100 %. Starting date 2025-01-01 or as agreed. Placement: Uppsala.

Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines.

For further information about the position, please contact: Associate professor Filip Malmberg, filip.malmberg@it.uu.se

Please submit your application by 26 of November 2024, UFV-PA 2024/3541.

Are you considering moving to Sweden to work at Uppsala University? Find out more about what it´s like to work and live in Sweden.

Type of employment Temporary position
Contract type Full time
First day of employment 2025-01-01 or as agreed
Salary Fixed salary
Number of positions 1
Full-time equivalent 100%
City Uppsala
County Uppsala län
Country Sweden
Reference number UFV-PA 2024/3541
Union representative
  • ST/TCO, tco@fackorg.uu.se
  • Seko Universitetsklubben, seko@uadm.uu.se
  • Saco-rådet, saco@uadm.uu.se
Published 17.Oct.2024
Last application date 26.Nov.2024 11:59 PM CET
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