Doctoral student in Computer Science with a focus on Efficient Methods for Machine Learning

Ref no: ORU 2.1.1-07578/2025

Örebro University and the School of Science and Technology are looking for a doctoral student in Computer Science. The position is expected to conclude with a doctoral degree.

Start date: Spring 2026.

The doctoral student will be affiliated with the Machine Perception and Interaction Lab at Örebro University, which carries out multi-disciplinary research at the intersection of artificial intelligence, robotics, machine learning, and human-robot interaction.

Project description

The focus of the project is machine learning and specifically the development of novel neuro-inspired and computationally efficient methods.

Modern machine learning methods often depend on enormous datasets and extensive computing resources. This trend limits their scalability, increases their environmental footprint, and makes advanced machine learning accessible only to those with significant computational power. Meanwhile, biological neural systems, such as insect or human brains, operate under extreme energy constraints yet still handle complex tasks remarkably well. They achieve this by leveraging such computational principles as structural organization, recurrence (memory over time), and even randomness.

Integrating these biological principles into machine learning opens a path toward methods that require far less computation while still delivering strong processing capabilities. To make this possible, both theoretical and practical advances are needed: a deeper understanding of how learning systems can build compact and selective memories, how they can leverage prior knowledge to interpret new data efficiently, and how state-of-the-art architectures like transformers could incorporate these principles to better handle challenges such as long-range temporal dependencies, limited training data, and restricted computing budgets.

The goal of the project is to explore how structured prior knowledge, memories of past inputs, and randomized representations can be combined to create high-performing machine learning models that run even on resource-constrained devices. This work aims to produce a new framework for lightweight machine learning: methods that remain competitive with state-of-the-art models while dramatically reducing computations. The project will demonstrate its impact in demanding challenging domains such as long-term forecasting of dynamical systems and the processing of biomedical signals from wearable devices.

The programme and the doctoral studentship

The doctoral programme consists of courses and an independent research project that has to be presented in a doctoral thesis. The programme concludes with a doctoral degree and comprises 240 ECTS credits, which corresponds to four years of full-time study.

The ambition is for your doctoral studies to be stimulating and purposeful throughout the programme until you obtain your doctoral degree. A thorough introduction will therefore get you off to a good start and provide a solid foundation on which you can build your studies. As a doctoral student at Örebro University, you will be offered a specially tailored seminar series within the subject of computer science, introduction to doctoral programme rules as well as opportunities for networking and career support during the doctoral programme.

The place on the programme is linked to a full-time doctoral studentship for the duration of the study programme, which corresponds to four years of full-time study. More information on doctoral studentships, part-time studies, and part-time doctoral studentships can be found in the Regulations Handbook. The initial salary for a doctoral studentship is SEK 32,300 a month.

The doctoral studentship is a tailored form of employment for students enrolled on a doctoral programme. It guarantees employment for the duration of the doctoral programme (given that the studies progress).

Entry requirements and selection

For admission to doctoral studies, applicants are required to meet both general entry requirements and specific entry requirements. In addition, applicants must be considered in other respects to have the ability required to benefit from the programme. For a full account of the entry requirements, please refer to the admissions regulations as well as to Annex 2 to the general syllabus for computer science.

Applicants meet the general entry requirements if they

1. Have been awarded a second-cycle qualification,
2. Have satisfied the requirements for courses comprising at least 240 ECTS credits, of which at least 60 ECTS credits were awarded in the second-cycle, or
3. Have acquired substantially equivalent knowledge in some other way in Sweden or abroad.

Applicants meet the specific entry requirements for research studies in computer science if they have been awarded a Degree of Master of Science in Engineering or a one-year Master’s degree from a programme within the subject field or related subjects, or if he or she has received a passing grade of at least 120 credits, including an independent project on the second cycle, in a main field of study of relevance to the computer science field. A person who has acquired substantially corresponding knowledge, in Sweden or abroad, also meets the specific entry requirements.

The successful candidate should demonstrate strong and independent problem-solving and critical analysis abilities. Furthermore, the candidate should have good cooperative and communicative skills. Fluent spoken and written command of English is essential, while knowledge of Swedish is not necessary. Having courses, a thesis, or publications in digital signal processing, electrical engineering, computer vision, machine learning, artificial intelligence, cognitive science, or robotics, is a merit.

Information

For more information about the programme and the doctoral studentship, please contact Dr. Denis Kleyko, e-mail: denis.kleyko@oru.se and Prof. Amy Loutfi, e-mail: amy.loutfi@oru.se. For administrative issues, please contact Prof. Martin Magnusson, e-mail: martin.magnusson@oru.se.

At Örebro University, each member of staff is expected to be open to development and change; take responsibility for their work and performance; demonstrate a keen interest in collaboration and contribute to development; as well as to show respect for others by adopting a constructive and professional approach.

Örebro University actively pursues equal opportunities and gender equality as well as a work environment characterized by openness, trust and respect. The qualities that diversity adds to operations are highly valued.

Application to the programme and for the doctoral studentship

The application is made online. Click the button “Apply” to begin the application procedure.

For the application to be complete, the following electronic documents must be included:

• Description of research interests - describing your research interests, explaining why you are interested in this project, and why you would be a good fit for the position (1 page)
• CV
• Proof that you meet the general and specific entry requirements (e.g., copies of the original certificate and official transcript for Bachelor's and Master's degrees)
• Independent project (degree project)
• Other relevant documents, course and degree certificates verifying eligibility

As a main rule, application documents and attachments are to be written in Swedish, Danish, Norwegian, or English. Certificates and documents in other languages verifying your qualifications and experience must be translated by an authorised translator to Swedish or English. A list of authorised translators can be obtained from Kammarkollegiet (the Legal, Financial and Administrative Services Agency), www.kammarkollegiet.se/engelska/start.

When you apply for admission, you automatically also apply for a doctoral studentship.
More information for applicants can be found on the university’s career page:  https://www.oru.se/english/career/available-positions/applicants-and-external-experts/

The application deadline is 2026-01-16. We look forward to receiving your application!

The university declines any contact with advertisers or recruitment agencies in the recruitment process.

As directed by the National Archives of Sweden (Riksarkivet), one file copy of the application documents, excluding publications, is required to be deposited for a period of two years after the appointment decision has gained legal force.