Örebro University is offering a fully funded PhD position in Computer Science, focusing on tractable quantum machine learning. This opportunity is based at the School of Science and Technology and is designed for candidates interested in the intersection of classical and quantum approaches to efficient inference in machine learning. The project aims to explore the foundations of tractable probabilistic models—those supporting efficient and exact reasoning—and to investigate their emerging connections to quantum machine learning. The research will delve into how principles such as structured computation and controlled expressivity, which make classical models tractable, can be extended or reinterpreted within a quantum information theoretic framework. The ultimate goal is to uncover unifying concepts that link classical and quantum models, paving the way for new, expressive, and computationally efficient machine learning paradigms.

The doctoral programme consists of both coursework and an independent research project, culminating in a doctoral thesis and the award of a PhD in Computer Science. The programme is structured as a full-time, four-year commitment (240 ECTS credits), with a clear introduction to doctoral studies, active participation in scientific seminars, and opportunities for networking and career development. Doctoral students benefit from a supportive academic environment and are encouraged to engage in conceptual work, prototype algorithm development, and contribute to the advancement of probabilistic and quantum AI.

The position comes with a full-time doctoral studentship, guaranteeing employment for the duration of the programme (subject to satisfactory progress). The initial monthly salary is SEK 32,300, and the studentship is tailored for doctoral candidates. Örebro University fosters an inclusive and respectful work environment, actively promoting equal opportunities and gender equality.

Applicants must meet both general and specific entry requirements. General requirements include a second-cycle qualification (Master's degree or equivalent), with at least 240 ECTS credits, including 60 credits at the second-cycle level. Specific requirements are a Master of Science in Engineering or a one-year Master's degree in computer science or related subjects, or at least 120 credits including an independent project in a relevant field. Equivalent qualifications from Sweden or abroad are accepted. The ideal candidate will have a strong background in probabilistic AI, linear algebra, and machine learning, with experience in quantum machine learning or tractable probabilistic models considered a significant advantage. Strong problem-solving, critical analysis, cooperative, and communication skills are essential. Fluency in spoken and written English is required; knowledge of Swedish is not necessary. Prior research experience, such as publications or involvement in scientific projects, is beneficial.

To apply, candidates should submit an online application including a description of research interests, CV, independent project/thesis, proof of meeting entry requirements, and other relevant documents. Documents must be in Swedish, Danish, Norwegian, or English, or translated by an authorised translator. The application deadline is January 12, 2026. For further information, contact Dr. Pedro Zuidberg Dos Martires ([email protected]) for academic queries or Prof. Martin Magnusson ([email protected]) for administrative matters. More details and the application portal are available at the university's career site.

This position is ideal for candidates passionate about conceptual research, abstract modeling, and the development of prototype algorithms in the rapidly evolving field of quantum machine learning.