Join Us!
The University of Amsterdam’s VISLab is looking for a Research Engineer to join the Toyota–UvA GAIA project, a 14-month industrial research programme developing the next generation of robot learning systems. You will work at the boundary of research and real-world implementation, translating cutting-edge computer vision and deep learning algorithms into working code that runs on real robotic arms. You will collaborate daily with postdoctoral researchers, PhD students, and engineers at Toyota Motor Europe and the Toyota Research Institute.
This is what you will do
As a Research Engineer, you are the technical backbone of the GAIA project’s sim-to-real pipeline — the critical link between physics-grounded simulation and real robot deployment. The project has already established a real-to-sim foundation: real environments can be reconstructed in 3D from video and images. Your focus is the next frontier: advancing sim-to-real transfer so that robot policies trained in simulation generalise robustly to real hardware. You will implement and test algorithms in Python and C++, integrate perception and control components with real Franka robotic arms, and work hand-in-hand with researchers to transform research prototypes into solid, reproducible software.
Tasks and responsibilities:
- implementing and extending the sim-to-real transfer pipeline, building on existing real-to-sim reconstruction infrastructure to enable robust robot policy deployment on real hardware;
- developing and integrating deep learning and computer vision modules (object detection, scene understanding, pose estimation) that bridge the gap between simulated and real-world perception;
- engineering the software interface between the physics simulation environment and physical robotic platforms (Franka), including sensor integration, calibration, and real-time control loops;
- profiling and debugging the end-to-end pipeline across simulation and hardware to identify and resolve failure modes, performance bottlenecks, and domain gap issues;
- collaborating closely with postdoctoral researchers and PhD students to translate research algorithms from prototype to deployable, well-tested code;
- building and maintaining ROS2-compatible software components and contributing to the shared robotics software architecture of the Toyota–UvA platform;
- conducting systematic benchmarking of learned robot policies in simulation and on real hardware, documenting results to support joint milestone deliverables with Toyota Motor Europe and the Toyota Research Institute;
- supporting the broader research team in keeping codebase, datasets, and experimental infrastructure well-organised and reproducible across the 14-month project duration.
What we ask of you
You are a hands-on engineer who enjoys solving hard technical problems at the boundary of software and hardware. You write clean, well-structured code, you are rigorous about testing, and nothing satisfies you more than watching a policy successfully transfer from simulation to a real robot arm. You stay composed when things break — and in robotics, things break — and you enjoy collaborating across the research–engineering boundary.
Your experience and profile:
- an MSc degree in Engineering, Artificial Intelligence, Computer Science, or a closely related field;
- strong programming skills in Python and C++, with a track record of writing clean, well-structured, and reproducible code;
- hands-on experience with deep learning frameworks, in particular PyTorch;
- solid understanding of computer vision concepts (object detection, pose estimation, image segmentation) and their practical implementation in real systems;
- strong problem-solving and debugging skills, with experience diagnosing issues across complex multi-component software and hardware systems;
- good communication and teamwork skills, with willingness to work at the interface of academic research and industrial engineering in a fast-paced international team;
- professional command of English (written and spoken).
- experience with ROS or ROS2 and real robotic platforms is a strong plus;
- familiarity with 3D vision, depth sensors, camera systems, or point cloud processing is a plus; experience with robot simulation environments (Drake, MuJoCo, PyBullet, Isaac Sim, or equivalent) is also welcomed.
This is what we offer you
We offer a temporary employment contract for 38 hours per week for a period of 14 months. The preferred starting date is as soon as possible.
The gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 3,382 to € 4,484 (scale 8) This does not include 8% holiday allowance and 8,3% year-end allowance. The UFO profile Engineering and application manager 5 is applicable. For this position we can not sponsor a visa. The Collective Labour Agreement of Universities of the Netherlands is applicable.
Curious about our extensive secondary benefits package? You can read more about it here.
You will work in this team
The Faculty of Science has a student body of around 8,000, as well as 1,800 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.
The position will be with Efstratios Gavves group and in very close collaboration with Toyota Core AI team. It is further embedded in VISLab, with more than 30 PhD students and postdocs working on theoretical and applied computer vision, deep learning, and Physical AI.
Want to know more about our organisation? Read more about working at the University of Amsterdam.
Do you want to build robots that learn — from simulation all the way to real hardware? If so, please continue reading!
Join Us!
The University of Amsterdam’s VISLab is looking for a Research Engineer to join the Toyota–UvA GAIA project, a 14-month industrial research programme developing the next generation of robot learning systems. You will work at the boundary of research and real-world implementation, translating cutting-edge computer vision and deep learning algorithms into working code that runs on real robotic arms. You will collaborate daily with postdoctoral researchers, PhD students, and engineers at Toyota Motor Europe and the Toyota Research Institute.
This is what you will do
As a Research Engineer, you are the technical backbone of the GAIA project’s sim-to-real pipeline — the critical link between physics-grounded simulation and real robot deployment. The project has already established a real-to-sim foundation: real environments can be reconstructed in 3D from video and images. Your focus is the next frontier: advancing sim-to-real transfer so that robot policies trained in simulation generalise robustly to real hardware. You will implement and test algorithms in Python and C++, integrate perception and control components with real Franka robotic arms, and work hand-in-hand with researchers to transform research prototypes into solid, reproducible software.
Tasks and responsibilities:
- implementing and extending the sim-to-real transfer pipeline, building on existing real-to-sim reconstruction infrastructure to enable robust robot policy deployment on real hardware;
- developing and integrating deep learning and computer vision modules (object detection, scene understanding, pose estimation) that bridge the gap between simulated and real-world perception;
- engineering the software interface between the physics simulation environment and physical robotic platforms (Franka), including sensor integration, calibration, and real-time control loops;
- profiling and debugging the end-to-end pipeline across simulation and hardware to identify and resolve failure modes, performance bottlenecks, and domain gap issues;
- collaborating closely with postdoctoral researchers and PhD students to translate research algorithms from prototype to deployable, well-tested code;
- building and maintaining ROS2-compatible software components and contributing to the shared robotics software architecture of the Toyota–UvA platform;
- conducting systematic benchmarking of learned robot policies in simulation and on real hardware, documenting results to support joint milestone deliverables with Toyota Motor Europe and the Toyota Research Institute;
- supporting the broader research team in keeping codebase, datasets, and experimental infrastructure well-organised and reproducible across the 14-month project duration.
What we ask of you
You are a hands-on engineer who enjoys solving hard technical problems at the boundary of software and hardware. You write clean, well-structured code, you are rigorous about testing, and nothing satisfies you more than watching a policy successfully transfer from simulation to a real robot arm. You stay composed when things break — and in robotics, things break — and you enjoy collaborating across the research–engineering boundary.
Your experience and profile:
- an MSc degree in Engineering, Artificial Intelligence, Computer Science, or a closely related field;
- strong programming skills in Python and C++, with a track record of writing clean, well-structured, and reproducible code;
- hands-on experience with deep learning frameworks, in particular PyTorch;
- solid understanding of computer vision concepts (object detection, pose estimation, image segmentation) and their practical implementation in real systems;
- strong problem-solving and debugging skills, with experience diagnosing issues across complex multi-component software and hardware systems;
- good communication and teamwork skills, with willingness to work at the interface of academic research and industrial engineering in a fast-paced international team;
- professional command of English (written and spoken).
- experience with ROS or ROS2 and real robotic platforms is a strong plus;
- familiarity with 3D vision, depth sensors, camera systems, or point cloud processing is a plus; experience with robot simulation environments (Drake, MuJoCo, PyBullet, Isaac Sim, or equivalent) is also welcomed.
This is what we offer you
We offer a temporary employment contract for 38 hours per week for a period of 14 months. The preferred starting date is as soon as possible.
The gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 3,382 to € 4,484 (scale 8) This does not include 8% holiday allowance and 8,3% year-end allowance. The UFO profile Engineering and application manager 5 is applicable. For this position we can not sponsor a visa. The Collective Labour Agreement of Universities of the Netherlands is applicable.
Curious about our extensive secondary benefits package? You can read more about it here.
You will work in this team
The Faculty of Science has a student body of around 8,000, as well as 1,800 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.
The position will be with Efstratios Gavves group and in very close collaboration with Toyota Core AI team. It is further embedded in VISLab, with more than 30 PhD students and postdocs working on theoretical and applied computer vision, deep learning, and Physical AI.
Want to know more about our organisation? Read more about working at the University of Amsterdam.
If you feel the profile fits you, and you are interested in the job, we look forward to receiving your application. You can apply online via the button below. We accept applications until and including 30 April 2026.
Applications should include the following information (all files besides your cv should be submitted in one single pdf file):
- a detailed CV including the months (not just years) when referring to your education and work experience;
- a letter of motivation;
- the names and email addresses of two references who can provide letters of recommendation.
Due to Dutch legislation, the UvA is for non-scientific positions obliged to recruit within the EU. If you are not a EU-citizen (including Norway and Switzerland) please do not apply for this vacancy.
Only complete applications received within the response period via the link below will be considered.
If you have any questions or do you require additional information? Please contact:
