Umeå University is one of Sweden’s largest higher education institutions with over 41,500 students and about 4,600 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.
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 key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here.
To our department, which conducts research at the highest international level and offers several high-quality educational programs in Computer Science, we are now seeking a PhD student with a focus on efficient evaluation of Tensor Networks.
The Department of Computing Science at Umeå University is an international environment for research and education covering a broad spectrum of computer science. The department is internationally renowned for its excellent research and education. We are affiliated with WASP – Sweden’s largest individual research program of all time, coordinate its sister program WASP-HS, which focuses on the consequences of emerging technologies, and are a strong partner in the national strategic research program eSSENCE. We value diversity and actively work to promote an inclusive work environment with a high level of engagement. Read more at: Department of Computing Science
Project description Tensors are the generalization of vectors and matrices to an arbitrarily large number of dimensions. Tensor Networks are representations of large tensors into networks of smaller ones. Originally used to estimate with high accuracy low-energy states of quantum many-body systems, in the last two decades Tensor Networks have emerged as a powerful and versatile computational tool in many disciplines, including quantum chemistry, materials science, quantum computing, and recently, interpretable machine learning. The computational capability of Tensor Networks was demonstrated in numerous scenarios, and many approaches for their evaluation have been proposed. However, high-performance libraries that are scalable with respect to both the size of the input data and the available resources (e.g., number of cores or GPUs) remain an unsolved problem.
The project focuses on the development of efficient algorithms for the parallel contraction of tensor networks, aiming to deliver a performance-portable software library. A model-based approach will be investigated, i.e., exploiting knowledge of the efficiency of the underlying computational building blocks. Further, for handling large-scale problems, the so-called “slicing technique” will also be considered. This research extends our previous work on Tensor Algebra Processing Primitives (TAPP, TAPPorg · GitHub).
The doctoral student will be part of the High-Performance and Automatic Computing group (HPAC), and jointly supervised by Paolo Bientinesi and Lars Karlsson. Furthermore, interdisciplinary collaborations with both industrial and academic partners are expected. HPAC’s webpage: High-Performance and Automatic Computing (HPAC)
Requirements The general admission requirements for doctoral studies are 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. To fulfill the specific entry requirements for doctoral studies in computing science, the applicant is required to have completed at least 90 ECTS credits in computer science. Applicants who otherwise have acquired skills that are deemed equivalent are also eligible.
Candidates for this position are expected to have solid foundations in numerical linear algebra, high-performance computing, parallel computing (MPI, OpenMP) and mathematical software. Proficiency in C/C++ is a requirement. It is a requirement that the candidate has prior experience with algorithms and libraries for tensor computations, and with BLAS. Familiarity with GPU programming is a merit, but not a requirement. Strong command of both written and spoken English language is a key requirement.
About the position The position provides you with the opportunity to pursue PhD studies in Computing Science for four years, with the goal of achieving the degree of Doctor in Computing Science. While the position is mainly devoted to PhD studies (at least 80% of the time), it may include up to 20% department service (usually teaching). If so, the total time for the position is extended accordingly, resulting in a maximum of five years.
Wage placement takes place according to the established salary ladder for doctoral student employment. According to the Higher Education Ordinance (Chapter 12, Section 2), the decision on employment cannot be appealed.
The candidate is expected to start as early as possible and no later than October 2026.
Application Applications must be submitted electronically using the e-recruitment system of Umeå University.
A complete application should contain the following documents:
A cover letter that motivates the interest in the position and that describes how the qualifications and experience are relevant to the employment (maximum 2 A4 pages with 11pt font). Applications without a meaningful cover letter will not be considered.
A curriculum vitae (CV).
Copies of degree certificates, including documentation of completed academic courses and obtained grades.
Reprints / copies of completed BSc and/or MSc theses and other relevant publications, if any.
Contact information for two reference persons.
Documentation and description of other relevant experiences or competences, including software projects.
The application must be written in English or Swedish. If attached documents are written in a different language, then a translation to English or Swedish must be included. Attached documents must be in pdf format. Applications must be submitted electronically using the e-recruitment system of Umeå University, and be received no later than 2026-05-25.
Selected applicants will be invited for an interview round, including a programming assignment.
For additional information, please contact Professor Paolo Bientinesi (pauldj@cs.umu.se).
Umeå University wants to offer an equal environment where open dialogue between people with different backgrounds and perspectives lay the foundation for learning, creativity and development. We welcome people with different backgrounds and experiences to apply for the current employment.
We kindly decline offers of recruitment and advertising help.
