Senior Researcher: Machine Intelligence - Theory of Large Language Models

Overview

The Machine Intelligence team at Microsoft Research Cambridge conducts foundational machine learning research across learning algorithms, model architectures, intelligent systems, and efficient AI.

We are seeking a Researcher to develop new theoretical foundations for understanding how and why modern machine learning models learn, generalize, and behave. The research may address areas such as training and optimization dynamics, feature and representation learning, the role of architecture, and scaling and emergent behaviour, with opportunities to connect theory closely to the team’s empirical research.

We seek a highly collaborative researcher with a solid record of original research, deep expertise in relevant areas of machine learning theory, and a commitment to impactful research. The role offers substantial scope to initiate and drive research directions while collaborating across theoretical and empirical research.

Responsibilities

• Develop and lead an original research programme in machine learning theory, with potential emphasis on the foundations of modern neural networks and foundation models.
• Develop mathematical frameworks that explain learning, generalization, optimization, representation learning, architectural effects, scaling, or other important aspects of modern machine learning.
• Contribute to the team’s broader scientific direction by identifying theoretically important questions arising from empirical research and using theory to motivate new algorithms, architectures, or experiments.
• Collaborate with researchers across Microsoft Research and the wider research community.
• Disseminate research through peer-reviewed publications, conference presentations, open scientific engagement, and collaboration with the broader research community.
• Mentor interns and less experienced researchers, providing guidance and feedback on their research and development.

Qualifications

Required/Minimum Qualifications

• A PhD in Machine Learning, Computer Science, Mathematics, Statistics, or a related field.
• Deep expertise and a solid record of original research in one or more areas of machine learning theory, such as learning theory, optimization and stochastic dynamics, high-dimensional probability and statistics, theoretical computer science, or the mathematical foundations of deep learning.
• Demonstrated ability to identify important research questions and independently drive research projects.
• Solid written and verbal communication skills, with the ability to explain complex ideas to a broad scientific audience and collaborate effectively across theoretical and empirical research.

Preferred/Additional Qualifications

• A sustained record of original, peer-reviewed research at leading venues in machine learning or theoretical computer science, such as COLT, NeurIPS, ICML, ICLR, STOC, FOCS, or SODA.
• Research that develops theoretical explanations for the behaviour of neural networks, foundation models, or other modern machine learning systems.
• Experience connecting theoretical analysis with empirical phenomena, experiments, or the design of learning algorithms and model architectures.
• Evidence of developing an original research agenda, leading research projects or collaborations, and mentoring less experienced researchers.

Research Sciences IC4 - The typical base pay range for this role across United Kingdom is £ 74,700.00 - £ 122,600.00 per year. Certain roles may be eligible for benefits and other compensation.

Find additional benefits and pay information here:
https://careers.microsoft.com/v2/global/en/corporate-pay/united-kingdom-corporate-pay.html

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.