Doctoral student in Computer Science

The School of Science and Technology at Örebro University is looking for a doctoral student in machine learning for the doctoral program in computer science, concluding with a doctoral degree (PhD. in Computer Science).

Start date: Summer / Fall 2025.

Project description

The research topic for this position is machine learning applied to one of the following focus areas of the Adaptive and Interpretable Learning Systems research group where the position is hosted:

• Reinforcement learning, focusing on task priorities, composability of tasks and policies, constraints, and transfer.
• Machine learning for counterfactual prediction and treatment effect estimation with large-scale observational data and deep learning models, focusing on countering selection bias, causal learning, identification of causal and irrelevant factors, and disentanglement of underlying variables.
• End-to-end learning for inverse optimization, focusing on identifying underlying cost models, learning from noisy observations, non-stationary and multi-modal data, differentiating through black-box optimizers and differentiable optimization, and representing uncertainty.
• Deep generative modeling of bio-medical data, focusing on identification of unknown chemicals/environmental pollutants from mass spectrograph data, predicting toxicity of compounds, in-silico models for replacing the need of animal studies, and representation learning for transfer between in-vivo and in-silico models.
• Spatio-temporal modeling of sensor and robotic data with probabilistic models, focusing on Gaussian Process Implicit Surface models, tomography data, sparse models, and model constraints.

Applicants need to indicate their topic preferences in the application.

The position will be funded by the Wallenberg AI, Autonomous Systems and Software Program (WASP), which 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.

Supervision

The doctoral student will be supervised by J. A. Stork (principal supervisor).

The program and the doctoral studentship

The doctoral program consists of courses and an independent research project that you will present in a doctoral thesis. The program concludes with a doctoral degree and consists of 240 credits, which corresponds to four years of full-time study.

The graduate school within WASP provides the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous systems and software. Through an ambitious program with research visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between PhD-students, researchers, and industry.

The place on the program is linked to a full-time doctoral studentship for the duration of the study program, which corresponds to four years of full-time study. The initial salary for a doctoral studentship is SEK 31 300 a month.

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 program. For a full account of the entry requirements, refer to the admissions regulations as well as to annex 2 (page 9-12) to the general syllabus for computer science.

Applicants meet the general entry requirements if they:

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

Applicants meet the specific entry requirements for doctoral 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 program 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 of at least 15 credits, in a main field of study of relevance to the computer science field. At least 30 credits of the 120 credits must have been awarded in the second cycle. A person who has acquired substantially corresponding knowledge, in Sweden or abroad, also meets the specific entry requirements.

A successful applicant should:

• be autonomous and show strong and independent problem-solving skills and critical analytical abilities,
• be fluent in spoken and written English,
• possess excellent programming skills,
• have a strong background in machine learning, computer science, and mathematics.

Experience with deep learning and the relevant software frameworks is another valuable merit. Prior knowledge in machine learning, reinforcement learning, deep generative models, Gaussian processes, probabilistic methods, and sensor data processing are beneficial.

Information

For more information about the program and the doctoral studentship, contact J. A. Stork (Johannes.stork@oru.se) or Martin Magnusson (martin.magnusson@oru.se).

At Örebro University, we expect each member of staff 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. We value the qualities that diversity adds to our operations.

Örebro University is internationally known for its expertise within artificial intelligence and robotics and is involved in several high-profile initiatives related to AI. Örebro University is highly active in the relevant European forums and platforms, and several EU-funded research projects. We are a modern, broad-based, and growing university. We endeavor to be an attractive place of work where members of staff feel a sense of pride and satisfaction. Currently, 1,600 employees and 17,000 students come to work and study at Örebro University.

Application to the program 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:

• Cover letter describing your research interests and how your background fits the position, including preference for the focus areas (max 1 page)
• CV with a relevant description of your overall qualifications and experience
• 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 degree)
• 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 authorized translator to Swedish or English. A list of authorized 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 will be found on our career site: https://www.oru.se/english/career/available-positions/applicants-and-external-experts/

The application deadline is 2025-04-14. We look forward to receiving your application

As we have already made our choices in terms of external collaboration partners and marketing efforts for this recruitment process, we decline any contact with recruitment agencies and advertisers.

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

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