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We are looking for a

Research assistant in Interpretable Machine Learning, at the Department of Computer Science and Media Technology, Faculty of Technology and Society.

Subject area

Interpretable Machine Learning for biomedical applications, particularly epileptic seizure prediction and detection. The project is positioned at the intersection of machine learning, biomedical signal processing, and responsible AI.

Job description

The work duties include conducting literature reviews on interpretable machine learning for biomedical applications, implementing interpretable ML models for epileptic seizure prediction and detection, and analyzing them using appropriate interpretability tools. The work also includes contributing to scientific publications and technical documentation. Additional duties within the project may arise.

Qualification requirement

Qualification requirements refer to requirements that must be met for an applicant to be considered for employment.

A research assistant must have a completed a degree on advanced level or equivalent expertise.

It is a general qualification requirement for teachers at Malmö University that the candidate is appropriate for and have the ability in general required to fully complete the duties of the relevant position.

 For this position, the specific requirements are

• A degree in Computer Science, Artificial Intelligence, Electrical Engineering, or a closely related field
• Strong programming skills in Python
• Familiarity with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch
• Excellent written and verbal communication skills in English
• Ability to work independently and collaborate in interdisciplinary research teams

Additional qualification requirements for this position are:

• Hands-on experience with biomedical signals (e.g., EEG, ECG) or other time-series data
• Hands-on experience in deploying machine learning models on microcontrollers or CPUs
• Proficiency in MATLAB
• Background or strong interest in interpretable/explainable AI
• to work independently and collaborate in interdisciplinary research teams 

Assessment criteria

Assessment criteria refer to criteria for assessing how well an applicant meets a certain qualification requirement and criteria that have otherwise been deemed significant for the position.

The overall assessment includes proficiency in the specific field relevant to the position.

For this position, the following will also be assessed:

For this position, the following will also be assessed: proficiency in Python and MATLAB; background or strong interest in interpretable/explainable AI, hands-on experience with biomedical signals, such as EEG or ECG, or other time-series data; and hands-on experience deploying machine learning models on microcontrollers or CPUs.

Assessment of qualifications will be done based on the adopted job description for the position. An overall assessment of the applicant’s qualifications and expertise based on the qualification requirements and assessment criteria will be made prior to a decision to hire an applicant.

Faculty

The Faculty of Technology and Society conducts education and research with a focus on technology and natural sciences at the two departments of Computer Science and Media Technology and Materials Science and Applied Mathematics. The faculty collaborates with companies and other organizations with the aim of raising the level of expertise, creating new products, developing businesses and giving students an early connection to their future working life. Our research collaborations and employees from a large number of countries give the activities an international character. More information about the faculty can be found here: Link

Department

The Department of Computer Science and Media Technology offers research-linked education at first-cycle, second-cycle and doctoral levels. The department conducts research in computer science, information systems, software engineering and media technology. We are interested in research and education areas such as artificial intelligence, digital media, e-health, internet of things and game development. Link

Application instructions

Apply for the position through Malmö University’s recruitment system by clicking on the “Apply” button. Application documents are to be submitted electronically. Physical documents are only accepted in exceptional cases; contact hr@mau.se if you have books or other documents that cannot be submitted electronically.

All qualifications are to be documented so that both quality and scope can be assessed. You are responsible for ensuring that your application is complete in accordance with the job description and application instructions and that it is submitted no later than 26 May 2026. The application is to be written in Swedish, English or one of the other Scandinavian languages. When required, you are responsible for translating the application and any submitted documents.

For guidance on compiling qualifications, you can use Academic Qualifications Portfolio at Malmö university,

The application is to include the following:

• Curriculum Vitae
• Degree certificates and other relevant grades and certificates
• A brief account of merits relevant to the position you are applying for, and how you, as an applicant, believe you can contribute.

Note that the documents submitted or produced for this open position (such as applications, expert reports and minutes) are normally general documents and as such public documents. This means that the documents may (except for documents classified as secret) be requested and read by others.

Terms of employment

Starts: 2026-06-01

Form of employment: Fixed-term employment for 5 months.

Scope of the employment: 40 %

Salary: Individual salary setting

Candidate availability and mutual agreement will be considered throughout the recruitment and employment process. At least one research assistant will be recruited through this process.

Swedish is the primary language at Malmö University, and it is a hope that non-Swedish speaking staff will acquire enough Swedish language skills to allow them to participate in teaching and research and in common and daily work at the department but also as a way to enable them to take on academic leadership positions.

Information

Azra Abtahi Fahliani, azra.abtahi-fahliani@mau.se

For questions about the recruitment process, contact HR Partner Magdalena Brossing, magdalena.brossing@mau.se

Trade union representatives

Saco-S: Jenny Vikman, jenny.vikman@mau.se

OFR/ST: Jelena Hovstadius, jelena.hovstadius@mau.se

Prior to this recruitment process, the Malmö University has determined which recruitment channels and marketing it will use. We request that no offers be made to provide advertising and recruitment help in connection with this advertisement.

We look forward to receiving your application!