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Research Internships at Spatial AI Lab Zurich, Switzerland Full-time Job

vor 1 Monat Engineering Zürich
Jobdetails

It has never been a more exciting time at the Spatial AI Lab in Zurich! Our team explores and incubates topics related to spatial computing, spatial AI and robotics. We are passionate about using computer vision to map and understand the environment, enable autonomous behaviour for robots, recognize and track relevant objects, and assist the user in performing the task at hand. We continue to advance the state of the art in Geometric Computer Vision, Machine Learning, Robotics, and Human / Environment Understanding. Everything we do is inspired by an underlying ethos of responsible development for AI systems, which in turn demands an inclusive approach to design that empowers everyone to do more. As an intern, you will have the opportunity to make a real contribution to our team’s efforts to shape the world. We are seeking Research Interns in Computer Vision, Machine Learning and Robotics, broadly defined, for our Spatial AI Lab in Zurich. As an intern, you will collaborate with one or more mentors and use the cutting-edge hardware and software technology we are creating. An internship at Microsoft will not only enhance your own career but enable you to participate in exciting research breakthroughs in the field. Interns work, learn, and network for life with some of the world’s top researchers and engineers.

Responsibilities

Interns apply their research skills and knowledge to practice. You will work on a stimulating and open-ended project that seeks to advance the cutting-edge during the 12-week internship. You will be required to work with other interns and researchers by frequently exchanging ideas and results with the group, proactively seeking feedback from others, working in a common codebase, and giving a final talk. Research internships are available in all areas, and run throughout the year, though they often start in the summer.

Qualifications

Required Qualifications

Must be currently enrolled in a PhD program in Computer Vision, Deep Learning, Robotics, Machine Learning, AI, or a related field.

Preferred Qualifications

Ideal candidates would have one or more of the following qualifications:

  • Student with at least a year of research experience in one of the following areas:
  • 3D scene reasoning with open vocabularies, Large Language Models (LLM), ...
  • SLAM, Structure-from-Motion, camera localization, image features, multi-view stereo, surface reconstruction
  • Mobile manipulation, robot-environment interaction
  • Human-robot interaction, particularly through natural language
  • human modelling, tracking, action and video understanding, human motion analysis
  • Deep generative modelling, and deep learning architectures
  • neural rendering and computer graphics
  • Skills in algorithmic problem-solving and software development (C++, Python, C#, etc.).
  • Experience with open-source tools such as PyTorch, Tensorflow, ROS, OpenCV, Unity, etc.
  • Familiarity with open-source 3D libraries such as COLMAP, Open3D, Theia, Maplab, etc.
  • Publication(s) in top-tier conferences or journals in related fields (e.g., CVPR, ECCV, ICCV, IJCV, PAMI, ICRA, IROS, RSS, IJRR, TRO, NeurIPS, ICML, etc.).
  • Excellent communication and writing skills.


Microsoft is an equal opportunity employer. Consistent with applicable law, 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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.