Research Student Assistant in Traffic Video Anomaly Understanding

KTH Royal Institute of Technology, School of Architecture and Built Environment

Job description

We are seeking a research student assistant interested in computer vision, video understanding, and multimodal artificial intelligence. The project addresses abnormal, risky, and assistance-requiring events involving vulnerable individuals, including people with disabilities, in traffic-related environments.

The assistant will help prepare traffic accident and fall-related video datasets, collect and annotate publicly available videos, and develop event labels for temporal boundaries, spatial locations, causes and severity. Tasks also include preparing question answer data, supporting the post-training and evaluation of a vision language model, assessing event detection and spatiotemporal localization, and documenting experiments and research results.

Qualifications

Requirements

You should be admitted to first or second-level cycle education at a Swedish university

Preferred qualifications

Student at KTH
Knowledge of Python, machine learning, and computer vision; experience in video processing, dataset preparation, or annotation is an advantage.
Experience with vision language models, PyTorch, model fine-tuning, video anomaly detection, or evaluation of AI systems is an advantage.

Great emphasis will be placed on personal skills.

Join us at KTH

KTH shapes the future through education, research, and innovation. As a leading international technical university, we play an active role in advancing the transition towards a sustainable society. At KTH, you have the opportunity to grow and develop in a creative and dynamic environment, with good working conditions and attractive benefits. Equality, diversity, and equal opportunities are essential to quality and form an integral part of KTH s core values as a university and public authority.

Learn more about our benefits and what it's like to work and grow at KTH

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Application

Log into KTH's recruitment system in order to apply for this position. You are responsible to ensure that your application is complete according to the instructions in the ad.

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CV
Transcript records

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About the employment

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Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence

Type of employment

Temporary position

Contract type

Part-time

First day of employment

1 November 2026 31 January 2027

Salary

Monthly salary

Number of positions

Full-time equivalent

50%

City

Stockholm

County

Stockholms l n

Country

Sweden

Reference number

PA-2026-3628

Contact

Yancheng Ling, Postdoc, yancheng@kth.se
Zhenliang Ma, Professor, zhema@kth.se

Published

2026-10-21

Last application date

2026-10-30