Job Specifications
Overview
For our Microsoft Research Cambridge (England, UK) lab we are seeking Research Interns in the area of Deep Learning, Generative AI and Decision Making Agents, with applications in Creative media, Robotics and Gaming. We encourage applications from all candidates with a background in World Modelling, Imitation and Reinforcement Learning, Foundation Models or a related field. If you are excited about exploring challenges that arise in real-world robotics applications and/or creative uses of current AI technology, and about working with experts from multiple disciplines to address some of these challenges, then we’d love to hear from you.
This is an exceptional opportunity to work closely with a highly collaborative and interdisciplinary team. The focus and scope of the project will consider the team’s direction as well as the experience and interests of the successful candidates.
Candidates must be enrolled in full-time study at a university and must be available for a 12-week internship in spring or summer 2026.
All candidates applying are considered on an equal basis. When submitting your application, include your CV with a list of publications. We encourage you to provide a brief cover letter notably highlighting topics and projects of interest. You will also be invited to submit contact details for a professional reference – these are optional but recommended. For more information about the post, please feel free to email Sergio Valcarcel Macua at sergiov@microsoft.com.
Responsibilities
In collaboration with your mentor and a diverse team, contribute to solving an ambitious research challenge and translate your results into actionable insights that are relevant to potential applications in creative media, robotics and gaming.
Write code and contribute to shared codebases to test the new approach or hypotheses.
Distil the developed insights into effective communications, such as a research paper, prototype, demonstration, presentation or another appropriate format to reach internal and external technical and general audiences.
Qualifications
Required/Minimum Qualifications:
Currently enrolled in a Masters or PhD program.
Research experience in at least one of the following or related areas: Generative models (world models, diffusion, autoregressive models) and controllability; Decision making, reinforcement and imitation learning (representation learning, planning, zero or few shot and sim-2-real generalization, fine-tuning foundation models); 3D computer vision (Gaussian splatting, NERF); Multi-modal representation learning; Training and fine-tuning large multimodal (including but not limited to vision-language) models.
Strong understanding of state-of-the-art deep learning approaches.
Hands-on experience in implementing and empirically evaluating deep learning approaches.
Effective communication skills and ability to work in a collaborative environment.
Preferred/Additional Qualifications
Currently enrolled in a PhD program in Artificial Intelligence, Machine Learning, Computer Science or a related area.
Ability to carry out research in at least one of the areas mentioned above, demonstrated by at least one journal or conference publication in one of the top publication venues in your research area.
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.