PhD Fellowship in Resource Efficiency for Generative AI
Join the University of Copenhagen to research sustainable, resource-efficient Large Language Models and AI agents.
Best for:Best for aspiring researchers with a strong background in machine learning, NLP, or information retrieval seeking a top-tier European PhD opportunity.
Overview
The Inference & Retrieval Lab within the Department of Computer Science (DIKU) at the University of Copenhagen invites applications for a fully funded PhD fellowship focusing on resource efficiency and sustainability in generative AI. The selected candidate will investigate algorithmic innovations, training paradigms, and hardware-aware optimizations to reduce the computational and energy footprints of Large Language Models and AI agents. Working alongside an internationally recognized team of researchers, the fellow will pursue an independent research agenda, publish in premier venues, and complete rigorous coursework. The position commences in January 2027 or as soon as possible thereafter.
What you'll do
- Conduct independent, high-impact research on resource-efficient and sustainable generative AI models and systems.
- Develop novel algorithms, training paradigms, prompting strategies, or hardware-aware optimization techniques for Large Language Models.
- Write scientific research papers targeting leading international conferences and journals.
- Complete PhD coursework corresponding to approximately 30 ECTS credits.
- Participate in teaching and dissemination activities as part of the academic duties.
- Engage with international research networks and undertake a research stay at an external institution, preferably abroad.
- Draft and successfully defend a comprehensive doctoral dissertation.
Requirements
Degree required: MSc or BSc degree in Computer Science or a closely related subject relevant to the research area.
Degree offered: PhD
Language: English; fluency in spoken and written English required.
Instruction: English
Publications: Relevant publications are desirable but not strictly mandatory.
- Strong academic background and high grades in Machine Learning, Natural Language Processing, Information Retrieval, or Recommender Systems.
- Demonstrated programming proficiency suitable for implementing advanced machine learning algorithms.
- Strong analytical skills with a demonstrated capacity for independent scientific inquiry and critical thinking.
- Strong academic writing and communication skills.
- Applicants must hold an educational background equivalent to either a relevant Danish master's degree (for the 3-year scheme) or a relevant bachelor's degree (for the 5-year integrated scheme).
- Minimum grade point average of 80% or equivalent.
Funding & terms
How to apply
Deadline: 2026-10-10 (CET)
Applicants must submit their complete application package electronically in English through the university's online recruitment portal before the stated deadline. The submission must include a one-page letter of intent, a detailed CV, transcripts and diplomas, and contact information for two referees.
- CV
- Letter of application
- BSc + MSc transcripts
- Original diplomas
- Publication list
- 3 reference letters
Contact
Christina Lioma· Professor
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