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. 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.

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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 seeks up to two postdoctoral researchers who will work in the Mathematical Foundations of Artificial Intelligence group under the supervision of Alp Yurtsever. The employment is full-time for two years starting from October 1st 2024, or by agreement. Apply latest 17 May 2024.

Project description and working tasks
The connection between optimization and machine learning is at the heart of many recent breakthroughs in artificial intelligence and autonomous systems. Many machine learning applications are modeled as optimization problems, and as problems become more and more complex, new optimization methods are needed. Within this framework, the successful candidate is encouraged to develop their research agenda in close collaboration with their supervisor. Potential areas of interest include, but are not limited to:

  • Efficient and scalable algorithms for machine learning,
  • Optimization problems with stochastic constraints,
  • Implicit regularization in neural networks,
  • Optimization with quantum computation,
  • Distributed optimization and federated learning,
  • Operator splitting methods in optimization,
  • Continual learning,
  • Bilevel optimization and applications in machine learning,
  • Representation learning,
  • Optimization on manifolds.

The project is part of the AI/MLX track of the Wallenberg AI, Autonomous Systems, and Software Program (WASP). WASP is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish society and industry. Read more: https://wasp-sweden.org/ 

Qualifications
To be appointed under the postdoctoral agreement, the postdoctoral fellow is required to have completed a doctoral degree or a foreign degree deemed equivalent to a doctoral degree. These qualification requirements must be fulfilled no later than at the time of the appointment decision.

To be appointed under the postdoctoral agreement, priority should be given to candidates who completed their doctoral degree, according to what is stipulated in the paragraph above, no later than three years prior. If there are special reasons, candidates who completed their doctoral degree prior to that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organisations, military service, or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant to the subject area. Postdoctoral fellows who are to teach or supervise must have taken relevant courses in teaching and learning in higher education.

Documented knowledge and proven experience in optimization or machine learning are required. In addition, good programming skills (preferably MatLab or Python) and communication skills in written and spoken English are required. A solid track record of publication and experience in optimization for machine learning are strong merits. The research tasks require independence, accuracy, and dedication.

Application
A full application should include: 

  • Cover letter in which you describe 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 (up to 2 pages plus references),
  • Curriculum vitae (CV) with publication list,
  • Verified copy of doctoral degree certificate or documentation that clarifies when the degree of doctor is expected to be obtained,
  • Verified copies of other diplomas, list of completed academic courses and grades,
  • Copy of doctoral thesis and up to 3 relevant articles, 
  • Other documents that the applicant wishes to present. 

Applicants selected for interviews will be asked to provide contact information to two persons willing to act as references. The application must be written in English or Swedish. The application is made through our electronic recruitment system. Documents sent electronically must be in Word or PDF format. Log in to the system and apply via the button at the end of this page. The closing date is May 17th, 2024. 

More information
Further details are provided by Alp Yurtsever, alp.yurtsever@umu.se, +46 90 7867546.

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

Type of employment Temporary position
Contract type Full time
First day of employment 2024-10-01
Salary Månadslön
Number of positions 2
Full-time equivalent 100%
City Umeå
County Västerbottens län
Country Sweden
Reference number AN 2.2.1-628-24
Contact
  • Alp Yurtsever, Associate Professor, +46907867546
Union representative
  • SACO, +46907865365
  • ST, +46907865431
  • SEKO, +46907865296
Published 19.Apr.2024
Last application date 17.May.2024 11:59 PM CEST
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