Uppsala University, Department of Information Technology

Are you interested in working with data-driven methods in control theory, 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, favorable working conditions? We welcome you to apply for a PhD position at Uppsala University. 

Uppsala University has a long tradition of successful research – among its alumni are 16 Nobel Prize laureates, including, most recently, Svante Pääbo. The University is unique when it comes to combining IT with wider research, from life sciences to the humanities, and this collaboration is currently facilitated by AI4Research and the Centre for Interdisciplinary Mathematics.

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, having around 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.

At the Division of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security.

The Division of Systems and Control enjoys a wide network of strong international collaborators all around the world, for example at the University of Cambridge, University of Oxford, Imperial College, University of British Columbia, University of Sydney, University of Newcastle and Aalto University. We strive for all PhD students to get a solid international experience during their PhD.

Project description
As more data are collected by industries and utilities around the world, there is an increasing interest in methods that can use this data to optimize control systems, maintenance strategies, and decision-making. 

This project is dedicated to the development and analysis of data-driven methods for decision and control of dynamical systems. It will utilize tools from control theory, estimation theory, and statistical learning, with the aim of generating new ideas that can be applied to a broad range of dynamical systems. The theoretical development will be grounded in key application areas, ensuring the practical relevance of our research in real-world settings.

The exact research topic is decided in a dialogue between the doctoral student and the supervisor. The position is funded by the Swedish Research Council.

Duties
A doctoral student will devote their time to graduate education mainly. The rest of the duties may involve teaching at the Department, including also some administration, to at most 20%.

Requirements

To meet the entry requirements for doctoral studies, you must

  • hold a Master’s (second-cycle) degree in engineering physics, electrical engineering, applied mathematics, or in a similar field, or
  • have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including an independent project worth at least 15 credits, or
  • have acquired substantially equivalent knowledge in some other way.

Information about the pecific entry requirements can be found in the study sullabus for the subject

We are looking for candidates with

  • a strong interest in automatic control and statistical learning,
  • good communication skills with sufficient proficiency in oral and written English,
  • excellent study results,
  • high proficiency in programming (preferably in Python or Matlab),
  • personal characteristics, such as a high level of creativity, thoroughness, and/or a structured approach to problem-solving are essential

Additional qualifications
Experience and courses in one or more subjects are valued: control theory, linear systems, signal processing, estimation theory, and system identification.

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

Application
The application must include: 
1) a statement (at most 2 pages) of the applicant’s motivation for applying for this position, including a self-assessment on why you would be the right candidate for this position; 
2) a CV;
3) degrees and transcript of records with grades (translated to English or Swedish); 
4) the Master’s thesis (or a draft thereof, and/or some other self-produced technical or scientific text), publications, and other relevant documents; 
5) references with contact information (names, emails and telephone number) and up to two letters of recommendation. 

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

About the employment
The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100 %. Starting date 1 November 2024 as agreed. Placement: Uppsala. 

For further information about the position, please contact: Associate Professor Per Mattsson (per.mattsson@it.uu.se), or Associate Professor Dave Zachariah (dave.zachariah@it.uu.se)..

Please submit your application by 30 August 2024, UFV-PA 2024/2432.

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 2024-11-01 eller enligt överenskommelse
Salary Fixed salary
Number of positions 1
Full-time equivalent 100%
City Uppsala
County Uppsala län
Country Sweden
Reference number UFV-PA 2024/2432
Union representative
  • ST/TCO, tco@fackorg.uu.se
  • Seko Universitetsklubben, seko@uadm.uu.se
  • Saco-rådet, saco@uadm.uu.se
Published 20.Jun.2024
Last application date 30.Aug.2024 11:59 PM CEST

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