Internship: Deep Learning for PointCloud Segmentation

Braincreators / Amsterdam (NL)

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Internship: Deep Learning for PointCloud Segmentation and Object Detection


At BrainCreators, we're at the forefront of applied AI with many years of successful research internship projects that combine cutting edge science with the challenges of applying AI in the real world. The focus of this year’s AI research internship projects will be on the technical challenges at the heart of our Machine Learning platform, BrainMatter.


What we expect from you

  • A full-time commitment to the research internship project.
  • A solid background in the theoretical subjects relevant for your particular project and ML coding skills in pyTorch.
  • Good communication and presentational skills, and a willingness to learn as much as possible in this exciting year.
  • Your project will have a scientific component on which you are encouraged to work towards a publishable paper at the end of the year.
  • Your project will also have an applied component, the result of which is a functional and documented piece of cutting-edge software that can be integrated into BrainMatter.
  • Bachelor’s degree in Artificial Intelligence or related field.

What we can offer you

  • The opportunity to work in our research team as a full time member.
  • A workplace in our Prinsengracht HQ with access to our compute cluster if required.
  • Support and supervision, including a weekly personal supervision meeting and research team group meeting as well as support for integration into our software stack when needed.
  • Internal weekly workshops about scientific and industrial progress.
  • Become part of a vibrant team of AI realists that know how to get things done.
  • Our best interns will be offered a full time job opportunity after graduation.

Project overview

At least three properties differentiate 3D PointCloud data from 2D images: PointCloud data is inherently unordered, there are more complex interactions among points, and it is invariant under different transformations. A naive Deep Learning approach that e.g., simply applies standard convolution to a voxelization of 3D space has drawbacks, and innovative approaches therefore focus on applying Deep Learning directly on the raw PointCloud data. The focus in this project is on understanding when and why to apply these latter techniques for our clients in the business of physical asset management. 

To help shape this roadmap we offer a research internship position in the area of object detection in PointCloud data, preferably combined with corresponding 2D visual input. The practical goal of the project is to both kickstart our work on Deep Learning for PointCloud in general, and work towards a software deliverable at the end of the project that has a focus on object detection or PointCloud segmentation functionality. At the same time, the research intern is encouraged to find and advance academic knowledge on this topic and work towards a publishable paper on graduation in collaboration with our team and University researchers. 

Read the full description and how you can apply here. 

Full description & Apply on site

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