Internship Opportunity: Alexandria

2 weeks ago


Cambridge, United Kingdom Microsoft Full time

In Project Alexandria, we automatically extract knowledge into a single, consistent knowledge base (KB). The KB is constructed by running a language model that summarizes the knowledge in a document, and then that knowledge is _linked _together to form a KB, collating mentions of the same knowledge entity from across the corpus. More machine learning models power _establishment_ and _quality_ in the KB. The KB then powers human-centric experiences that enable people to work effectively with knowledge, helping them find projects, people and information across their company. Our team video explains more. The Alexandria team includes experts in Machine Learning, HCI and software engineering, who work together to being ML-powered human-centric experiences to users through products like Viva Topics and Enterprise Copilots. Central to the team’s mission is the advancement and incorporation of new machine learning technologies that empower richer experiences for users.

We have three available positions, each to study one of:

- Knowledge Base powered Large Language Models
- Generative models for knowledge linking
- Compressed transformers for high throughput knowledge extraction.

You will join our ambitious research team for summer 2024 in Cambridge (UK).

**Responsibilities**:
As a member of the Alexandria team, you will play an important role in realizing our ambitions for the future of AI-assisted knowledge work. Working closely together with other team members, and supported by a group of skilled engineers, you will take part in conceiving, implementing, and testing new ideas that can revolutionize how institutional knowledge is accessed within the enterprise.

During the 12-week Internship you will:

- Advance state-of-the-art in enterprise knowledge modelling
- Work with internal and external collaborators
- Report and present research findings within Microsoft Research.
- Report findings in research publications.

**Qualifications**:

- Currently enrolled in a PhD program in Machine Learning, Deep Learning, or related technical field.
- Experience and interest in one or more of the following areas: deep generative models (e.g., diffusion models or large language models), probabilistic machine learning, model compression, and knowledge modelling.
- Ability to write reproducible and reusable research code, as evidenced by for example previous projects or public GitHub profile.
- Experience with research tools including git and python, as well as a python-based deep learning stack such as PyTorch or TensorFlow.
- Good scientific writing ability, as evidenced by published papers at top ML conferences, or equivalent experience.
- The ability to work in a diverse and multidisciplinary team.



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