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ABB

Thesis Work for generating photo realistic virtual training data for physical AI models

AI in this role

Thesis student role researching physical AI models and robotic simulation using Gaussian Splatting and Transformers at ABB Robotics.

Gaussian SplattingTransformersPyTorchCAD

At ABB, we help industries outrun - leaner and cleaner. Here, progress is an expectation - for you, your team, and the world. As a global market leader, we’ll give you what you need to make it happen. It won’t always be easy, growing takes grit. But at ABB, you’ll never run alone. Run what runs the world.

This role sits within ABB's Robotics business, a leading global robotics company. We're entering an exciting new chapter as we’ve announced the plan for SoftBank Group to acquire ABB Robotics. SoftBank is a globally recognized technology group and investor/operator focused on AI, robotics, and next-generation computing. By joining us now, you’ll be part of a pioneering team shaping the future of robotics—working alongside world-class experts in a fast-moving, innovation-driven environment.

This Position reports to:

R&D Team Lead


Your role and responsibilities

The thesis focuses on exploring the performance of physical AIs trained on virtually generated video reference.

Details:

  • Period: January - June 2027
  • Number of credits: 30 ECTS/högskolepoäng (hp)
  • Number of students for this thesis work: Two
  • Location: Partly on-site

Physical AI models require large amounts of training data when training for a task.

Your responsibilities:

  • Research different solutions of simulating robots and their ability to capture video footage en masse.
  • Create 3D digital twins of robot-setups using state-of-the-art techniques, such as Gaussian Splatting/Triangle Splatting, mesh generation, etc.
  • Evaluate performance of robots using physical AI methods, such as ACT (Action Chunking with Transformers), trained on virtually generated video reference.
  • Explore what level of fidelity is needed from a simulation to successfully train an AI model, with the objective to find a balance between speed, implementation complexity, and performance.


Qualifications for the role

  • Engineering student with background in robotics, computer science, or program with similar profile.
  • Experience with machine learning and AI training, preferably in the fields of AI vision systems or imitation learning.
  • Knowledge about linear algebra.
  • Experience with 3D rendering and CAD and/or 3D modelling techniques is a plus.
  • Hands-on experience with ABB industrial robots is a plus.

More about us

Recruiting Manager Stefan Westberg, +46724613140, will answer your questions.

Positions are filled continuously. Please apply with your CV, academic transcripts, and a cover letter in English.

We look forward to receiving your application!

A Future Opportunity
Please note that this position is part of our talent pipeline and not an active job opening at this time. By applying, you express your interest in future career opportunities with ABB.

We value people from different backgrounds. Could this be your story? Apply today or visit www.abb.com to learn more about us and see the impact of our work across the globe.

How we rate this

Thesis Work for generating photo realistic virtual training data for physical AI models at ABB rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Gaussian SplattingTransformersPyTorchCAD

Questions you could be asked

  1. What's a project where you used Gaussian Splatting hands-on?
  2. Walk me through how you've used Transformers in your day-to-day work.
  3. What are the limits of PyTorch that you've run into, and how did you work around them?
  4. What's a project where you used CAD hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: Gaussian Splatting, Transformers, PyTorch, and CAD. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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