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Samsung Intern Researcher Computer Vision Machine Learning United Kingdom, England, Cambridge 236176765
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Role and Responsibilities
Samsung AI Centre (AIC-Cambridge) are looking for exceptional interns to undertake a 6-month internship programme during 2025.
Future Interaction Lab:Vision & language, large scale model training, video understanding, image generation.
Embedded AI Lab:Efficient foundation model architectures, AutoML, Model compression, Speech Recognition and Generation, NPU Hardware design, diffusion models.
Machine Learning/Data Intelligence Lab:Meta-learning, In-Context Learning and LLMs, Neuro-Symbolic Learning, Neural Rendering.
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.
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 AIC-Cambridge topics of interest summarised above.
Contract Type:6 Month Internship
Hybrid Policy: 3 days onsite and 2 days working from home weekly
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