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    4. Cambridge Residency Program TaiX ML Residency PhD 2025
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    The Teachable AI Experiences (TaiX) team at Microsoft Research Cambridge (UK) is a multidisciplinary research group that brings together different skill sets to innovate human-AI interaction.

    The role

    The team is hiring a machine learning (ML) researcher to push the state-of-the-art of generative AI systems, with a goal of ensuring equitable experiences for all. The candidate should have deep technical knowledge of current generative AI models, with a particular focus on multi-modal models (e.g. image-text models like GPT-4Vision, LLaVa and CLIP). They should be able to approach technical problems in a multi-disciplinary way, and be passionate about building AI technologies that will ensure the inclusion of marginalised communities.   

     Responsibilities

    • Undertake cutting-edge research in deepening our understanding of generative AI models, including the development of technical approaches to ensure they perform equally well in all scenarios.  
    • Write research code to develop and validate new approaches, or develop novel theoretical and practical insights.  
    • Collaborate with a diverse and multi-disciplinary team.  
    • Clearly communicate research ideas and results in writing, such as research papers, presentations, or research notes for internal and external audiences.  

    Qualifications

     Required/Minimum Qualifications:   

    • PhD in Machine Learning, Deep Learning, or a related area.  
    • Strong technical understanding of state-of-the-art generative AI models, with a particular focus of multi-modal models.  
    • Demonstrable ability to drive high-quality research insights through publications in top-tier machine learning conferences and journals (e.g. NeurIPS, ICML, ICLR, AAAI, ICCV, ECCV, CVPR, JMLR).  
    • Hands-on experience in implementing and empirically evaluating deep learning approaches in PyTorch.   
    • Effective communication skills and ability to work in a collaborative environment.   

    Preferred/Additional Qualifications: 

    • Demonstrable research expertise in any of the following fields: AI fairness, AI interpretability and/or transparency, model adaption (e.g. PEFTs), data-centric AI, evaluation methods.  
    • The ability to approach technical problems and design solutions with a multi-disciplinary perspective.  
    • Passion for ensuring the inclusion of marginalised communities in AI technologies.  
    • Previous experience working in a multi-disciplinary team with diverse skill sets.  
    • Contribution to open-source code projects (e.g. on GitHub).