Intern - AI Research

Position Summary

SAIC Cambridge are looking for exceptional interns to undertake a 6-month internship programme during 2026.

The successful candidates will work within a world-class cross-disciplinary research centre, collaborating with researchers and engineers in basic and applied research across the centre to with the aim of publishing research in top conferences, filing patents, sharing reproducible code to the broader AI community on GitHub, and contributing to commercial tech transfers. Interns will be affiliated to one of the three labs within Cambridge and will be assigned senior mentors to help develop skills, and guide the generation of publications and impact. Topics of interest include, but are not limited to the following:

Future Interaction Lab: Vision & language, multi-modal language models, large scale model training, vision-language-action models.

Embedded AI Lab: World models & physical AI, Efficient foundation model architectures, Speech Recognition and Generation, image/video generation models.

Machine Learning/Data Intelligence Lab: World models for planning & reasoning. Inverse Graphics and Inverse Physics. Meta-learning. Neuro-Symbolic AI.

Role and Responsibilities

Key Responsibilities:

• Conduct cutting-edge research to develop state-of-the-art solutions to existing problems and/or propose novel research challenges considering real-world case studies in AI.
• Publish in top-tier conferences and journals, such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, AAAI, ACL, InterSpeech, etc.
• Development of high quality code with detailed documentation to support reproducible research in local and international research communities in AI.

Skills and Qualifications

Essential Skills & Qualifications

Currently studying for a PhD in Computer Science, Engineering, Mathematics or a related discipline (or just completing). Good command of computing concepts (algorithms, data structures, parallel/distributed computing, optimization, etc). Experience in quick prototyping using Python and PyTorch. At least one first-author publication in top conferences and journals such as: NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, AAAI, InterSpeech, EMNLP, ACL, MobiComm, etc.

Desirable Skills

Experience and demonstrated output on Foundation Models research involving (visual) LLMs and/or Diffusion models. Experience in software engineering & development in a professional environment. Experience with distributed GPU implementation of ML algorithms Experience with on-device implementation of ML algorithms. Experience in one or more of SAIC-Cambridge topics of interest summarised above.

Start date: ASAP

Duration: 6 months

Hybrid Policy: 3 days on site (minimum) 2 days working from home

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