Research Intern (AML-Algorithm) - 2026 Start (PhD)

What you'll do

• Research recommendation methods, including large-scale and generative recommendation or reinforcement learning for personalization.
• Prototype modeling strategies using multimodal data and investigate long-term user behavior.
• Test research ideas with collaborators and share findings through presentations, reports, or publications.

What they ask for

• Currently pursuing a Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
• Strong research background in machine learning, deep learning, recommender systems, or related areas.
• Proficiency in Python or C++, and familiarity with PyTorch or TensorFlow.
• Solid understanding of modern ML methods such as transformers, LLMs, or multimodal learning; ability to conduct independent research.

Nice to have

• Prior research or publications at top-tier ML/AI conferences such as NeurIPS, ICML, ICLR, KDD, RecSys, or WWW.
• Experience with large-scale ML systems or end-to-end ML pipelines.

Tools

Python, C++, PyTorch, TensorFlow, transformers, LLMs

AI focus

Machine-learning research for recommendation and personalization, including generative recommendation, reinforcement learning, multimodal modeling, and long-term user behavior.