Machine Learning/Computer Vision (PhD) - Cambridge (Hybrid)

We have 1 position open in the broad areas of Machine Learning and Computer Vision with a focus on Vision and Language. The positions are part of the Future Interaction Research Programme. Our topics of interest include but are not limited to:

• Contrastively-trained and auto-regressive Vision & Language (e.g. CLIP, BLIP).

• Visual LLMs (e.g. LLaVA).

• Generative Models (e.g. Stable Diffusion and Auto-Regressive models).

• Efficient Architectures.

• Model Compression (distillation, quantization).

• Efficient Adaptation of Large Models.

Key Responsibilities:

• Conduct hands-on innovative research, including methodological conceptualization and implementation.

• Publishing at top venues: CVPR, ECCV, ICCV, ICLR, NeurIPS, ICML, EMNLP, ACL, TPAMI and IJCV.

• Contribute to the research agenda and directions within the center.

• Interact with product and engineering teams for the purpose of technology transfer.

Skills and Qualifications

Key Skills Required:

• Research experience in the fields of Computer Vision and/or Machine Learning.

• Familiarity with fast prototyping Deep Learning frameworks such as PyTorch.

• A track record of publishing at top-tier venues (e.g. CVPR, ECCV, ICCV, ICLR, NeurIPS, EMNLP, ACL, ICML, TPAMI and IJCV).

• Ability to communicate well and to collaborate with other group members.