Cambridge Residency Program - Knowledge Representation in Generative Models
Microsoft, Newtown, Cambridge
Cambridge Residency Program - Knowledge Representation in Generative Models
Salary not available. View on company website.
Microsoft, Newtown, Cambridge
- Full time
- Permanent
- Onsite working
Posted 2 weeks ago, 5 Dec | Get your application in now before you miss out!
Closing date: Closing date not specified
job Ref: e49575e0d8d6417d9360d9a864de262f
Full Job Description
- Develop and drive an ambitious research agenda in machine learning andknowledge representation.
- Work closely in a team of machine learning researchers and software engineers to ideate and implement novel models and experiences.
- Collaborate with product groups across Microsoft to rapidly deploy the novel research in real-world applications and ensure its effectiveness in the live system.
PhD in machine learning, statistics, or a related field, or equivalent experience. - Strong software design and implementation skills with an object-oriented programming language such as Python, C#, etc.
- Growth mindset, curiosity about learning new things and a desire to deeply understand AI systems from a first-principles view.
- Drive for results.
- Passion to see research having impact on enterprise applications.
- Ability to work in a multi-disciplinary team. Preferred :
- Publication record in relevant conferences, such as NeurIPS, ICML, ICLR, KDD, etc.
- Expertise in deep learning,generative modelling (e.g.diffusion models).
- Experience with productizing machine learning research.
Microsoft Corporation Cambridge Residency Program - Knowledge Representation in Generative Models in Cambridge, United Kingdom Come and work with us to shape the future of AI and machine learning! The Alexandria team at Microsoft Research Cambridge (UK) invites machine learning and AI researchers with a focus on structured knowledge and generative modelling to join our two-year Residency Program. Alexandria is a research project which aims to deliver the next breakthrough in AI by combining our expertise in knowledge representation with the latest advancements in generative modelling of text, images, and videos. We develop novel methods and models to construct and evaluate consistent and rich knowledge graphs using large GPU clusters and then integrate them into Microsoft's Copilots at scale. From a fundamental understanding of large language models (LLMs) to modelling knowledge and workflows in personal data, our work has broad scope. This includes creating and scaling the best models and experiences for all our users by collaborating with other ML research teams, social scientists, designers, and product group partners across Microsoft. We also publish (e.g. DiSK (https://arxiv.org/abs/2312.05253) , MuSEE (https://arxiv.org/abs/2402.04437) , KBLaM (https://arxiv.org/abs/2410.10450) ) and open source (e.g. MuSEE (https://github.com/microsoft/Structured-Entity-Extraction/) ) our work. This is an exceptional opportunity to drive ambitious machine learning research while collaborating with domain experts to push the state of the art in knowledge and process automation with the potential for enormous real-world impact.