Cambridge Residency Programme - Post-Doctoral Researcher in Machine Learning - People-Centric AI

The successful candidate will design and implement methods to improve human AI collaboration, such as integrating human feedback into model development, applying reinforcement learning, and modelling decision making processes. They will contribute to the finetuning of large language models, publish at top research venues, and translate findings into technical and design insights that shape future AI systems.

• A PhD in a relevant field (e.g. ML, Computer Science, Mathematics) or equivalent industry experience.
• Expertise in ML, evidenced by top-tier publications and/or experience.
• Demonstratable experience in conceptualizing, implementing and evaluating machine learning approaches.
• Ability to clearly communicate your research to a diverse audience.
• Motivated to tackle technological problems rooted in real-world human needs, including an interest in how AI systems interact with people and society, and a commitment to designing inclusive, socially impactful technologies.
• Collaboration skills - the candidate can iterate their technical solutions with feedback from the team/users, rather than seeking to solve problems independently.

Preferred/Additional Qualifications:

• Broad ML education and experiences, covering, for example: statistical methods, probabilistic modelling, RL, deep learning, LLM training, decision-making processes.
• Experience with multi-modal models and world models.
• Strong ML coding and engineering skills., * Publications at top research venues in machine learning, artificial intelligence, natural-language processing, or adjacent areas.
• Completed or on track to a PhD in ML or have equivalent industrial experience.

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

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