Doctoral student in Feminist AI Addressing Gender-Based Violence
KTH Royal Institute of Technology is offering a fully funded doctoral position in
Feminist AI Addressing Gender-Based Violence
within the Department of Computing and Learning Systems (CLS). The position is based in Stockholm, Sweden, and is part of KTH’s third-cycle subject in Information and Communication Technology.
The project sits at the intersection of
artificial intelligence, machine learning, natural language processing, and social justice
. Its aim is to develop new AI methods that can make online gender-based violence visible—not only by detecting explicit abuse, but also by identifying structural silences, omissions, missing voices, and hidden patterns that shape digital narratives. The project will involve building novel ML models and evaluation methods, creating large-scale datasets and knowledge graphs, and collaborating with feminist organizations and civil society partners.
The successful doctoral student will contribute to research on responsible, transparent, and socially aware AI systems, with opportunities to publish in leading AI venues. The research environment is described as interdisciplinary, collaborative, and strongly committed to scientific excellence, intellectual curiosity, diversity, and social impact.
Supervision
is provided by Associate Professor Amir Hossein Payberah.
Eligibility requirements
include a second-cycle degree (for example a master’s degree), or at least 240 higher education credits including 60 second-cycle credits, or equivalent knowledge. Applicants must also demonstrate English proficiency equivalent to English B/6. KTH additionally values the ability to work independently and collaboratively, take a professional approach, and analyze complex problems.
Funding
is fully provided through the doctoral employment, with salary according to KTH’s doctoral student salary agreement. The position is a full-time temporary doctoral appointment.
Application
is made through KTH’s recruitment system. Required documents include diplomas and grade transcripts, proof of language requirements, a CV, a motivation letter describing research interests and goals, representative publications or technical reports, and contact information for two to three academic references. The deadline is 2026-09-24 at midnight local time.
