PhD Student in Algorithmic Foundations of AI-Assisted Consensus and Ranking
Develop novel algorithms for crowd consensus and content ranking using axiomatic approaches and human-AI collaboration.
Best for:Best for computer science and data science graduates with a strong mathematical background and an interest in social choice theory and algorithms.
Overview
The KTH Royal Institute of Technology invites applications for a fully-funded PhD position in Computer Science, focusing on the algorithmic foundations of AI-assisted consensus and ranking. Supervised by Prof. Aristides Gionis, the successful candidate will work on developing new methods for content selection and ranking through crowd consensus using interaction data and social choice theory, without editorial discretion. This position is part of the Wallenberg AI, Autonomous Systems and Software Program (WASP) graduate school, offering an interdisciplinary environment and strong networking opportunities. The candidate is expected to pursue independent research, collaborate with international partners, and contribute to graduate-level education and administration tasks up to 20%.
What you'll do
- Develop novel algorithms for content selection and ranking based on crowd consensus and interaction data
- Apply axiomatic approaches and social choice theory to model human-AI collaboration in content moderation
- Conduct independent research and publish findings in peer-reviewed venues
- Participate in the WASP graduate school activities, research visits, and networking events
- Engage in limited departmental duties such as teaching assistance and administrative tasks up to 20% of the workload
Requirements
Degree required: Master of Science degree in computer science, machine learning, AI, data science, or a related area
Degree offered: PhD
Language: English equivalent to English B/6
Instruction: English
- Strong mathematical background with solid academic credentials
- Proficiency in algorithm design and analysis
- Ability to pursue independent research and tackle complex analytical problems
- Strong communication and collaborative skills
- Passed a second cycle degree (master's degree) or completed course requirements of at least 240 higher education credits including 60 second-cycle credits
Funding & terms
How to apply
Submit your application through the KTH recruitment portal by the specified deadline. Ensure all academic transcripts, CV, and supporting documents demonstrating your mathematical and computer science background are attached.
- CV
- Master of Science degree certificate and transcripts
- Cover letter
- Reference letters
Contact
Aristides Gionis· Professor
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