Thesis Work -Depth-Aware Physical AI Models for Robot Manipulation
AI in this role
Conduct thesis research on incorporating depth information into Vision-Language-Action models for robot manipulation.
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 Center LeadYour role and responsibilities
Physical AI models such as Vision-Language-Action (VLA) models have recently emerged as a promising approach to robot automation. Unlike traditional robot programming, VLA models learn robot manipulation tasks directly from human demonstrations. They take camera images and language instructions as input, and output robot actions directly. Currently, most VLA models rely solely on standard RGB (color) images, which lack explicit spatial and geometric information about the environment.
This thesis investigates how to incorporate depth information (e.g., from RGB-D cameras) into VLA or other physical AI models to improve robot manipulation performance.
The student is expected to:
- Survey existing approaches for integrating depth/3D information into VLA or other physical AI robot manipulation policies
- Design and implement one or more methods to incorporate depth into a VLA or other physical AI model (e.g., as an additional input modality, via 3D representations, or point clouds, etc)
- Evaluate performance on real robot manipulation tasks in ABB's lab environment
- Document findings and contribute to ABB's Physical AI pipeline
The student is encouraged to propose their own ideas on how depth information can best be represented and utilized within the model.
Details:
- Period: January to July, 2027
- Number of credits: 30 ECTS/högskolepoäng (hp)
- Number of students for this thesis work: 1
- Location: on-site, Västerås
Qualifications for the role
- Master's student in Computer Science, Electrical Engineering, Robotics, Mechatronics, or other related fields
- Strong interest in robot learning, machine learning, computer vision, or physical AI
- Programming experience in Python and familiarity with deep learning frameworks (e.g., PyTorch, huggingface, LeRobot platform).
- Experience with git, docker, etc is a plus.
- Experience with or interest in 3D data (depth images, point clouds) is a plus
- Hands-on experience with real robot systems is a plus but not required
- Ability to work independently and communicate findings clearly
More about us
Recruiting Manager LiWei Qi, +46 73 021 2309, Supervisor: Chi Zhang, chi.zhang@se.abb.com , Marco Iannotta marco.iannotta@se.abb.com 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 -Depth-Aware Physical AI Models for Robot Manipulation at ABB rates 90 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.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Tell me about a project where robotics was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where physical ai was part of your work. What did you do?
- Tell me about a project where vla models was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Computer Vision, Robotics, Machine Learning, Physical AI, and Vla Models. 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.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get a free CV reviewGet new AI jobs (Builds AI ●●●●) by email
One email a week with the new AI jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Other roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step