Applied Sciences Intern

8 Months ago • Upto 1 Years

Research Development

Job Description

This Applied Sciences Internship at Microsoft Research focuses on advancing geometric computer vision using geometric algebra. Interns will develop and implement deep learning models for computer vision and robotics applications, enhancing techniques for visual odometry, feature extraction, and object recognition. Responsibilities include implementing SLAM algorithms for real-time environment mapping and robot localization, integrating optical flow methods for motion estimation and navigation, and leveraging geometric algebra to improve the efficiency and accuracy of spatial transformations. The internship offers a dynamic environment within a network of world-class research labs, contributing to cutting-edge advancements in AI and related fields.

Must Have:

PhD registration
Deep learning model development
Geometric computer vision expertise
SLAM algorithm implementation
Optical flow integration
Geometric algebra application

Perks:

Industry leading healthcare
Educational resources
Discounts on products and services
Savings and investments
Maternity and paternity leave
Generous time away
Giving programs
Networking opportunities

Add these skills to join the top 1% applicants for this job

algorithms

computer-vision

deep-learning

innovation

lqa

Overview

Research Internships at Microsoft provide a dynamic environment for research careers with a network of world-class research labs led by globally-recognized scientists and engineers, who pursue innovation in a range of scientific and technical disciplines to help solve complex challenges in diverse fields, including computing, healthcare, economics, and the environment.

Recent advances in AI have been driven in great part by developments in computer vision. However, geometric computer vision, a subarea of great importance to key applications such as autonomous driving, robotics, and augmented reality, has not benefited from this revolution - today, most problems in geometric computer vision are still solved through classical methods. In this project, we will explore how methods based on the formalism of geometric algebra can help in closing this gap. Specific topics include:

Geometric algebra methods for deep optical flow computation.
Direct application of deep learning in geometric algebra estimation.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Qualifications

Required Qualifications:

Must be registered to a PHD program.

Responsibilities

Develop and Implement Deep Learning Models: Design, train, and optimize machine learning and neural network models for applications in computer vision and robotics, ensuring high performance and accuracy.
Enhance Geometric Computer Vision Techniques: Apply advanced algorithms for tasks such as visual odometry, feature extraction, and object recognition, leveraging geometric principles to improve system robustness and accuracy.
Implement SLAM (Simultaneous Localization and Mapping): Develop and optimize algorithms for real-time environment mapping and robot localization, ensuring seamless navigation and object tracking in dynamic environments.
Integrate Optical Flow and Visual Navigation Systems: Design and integrate optical flow methods to enable precise motion estimation, visual-based navigation, and dynamic obstacle avoidance for autonomous systems.
Leverage Geometric Algebra for Advanced Computing: Utilize geometric algebra (Clifford algebra) to improve the efficiency and accuracy of spatial transformations, rotations, and other geometric operations in computer vision and robotics tasks.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

Industry leading healthcare

Educational resources

Discounts on products and services

Savings and investments

Maternity and paternity leave

Generous time away

Giving programs

Opportunities to network and connect

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