RESEARCH ASSISTANT POSITION ON AUTONOMOUS DRIVING
Call reference: 20260202_ADLab
Closing date: 12/02/2026
ABOUT CVC
The Computer Vision Center (CVC) is a non-profit research center established in 1995 by the Generalitat de Catalunya and the Universitat Autònoma de Barcelona (UAB). Its mission is to carry out cutting-edge research that has the highest international impact in the field of computer vision. It also promotes the transference of knowledge to industry and society.
Computer vision is an exciting research area and an omnipresent technology, essentially empowering machines with the sense of vision. The CVC is a successful marriage between knowledge and innovation. In addition to our cutting-edge scientific achievements, we have established lasting ties with industrial partners and created several spin-off companies.
CONTEXT AND MISSION
We are seeking an undergraduate or master-degree research assistant to collaborate on CARLA project, developing training and evaluation methodologies for Autonomous Driving systems. The position requires knowledge of Deep Learning as well as physics related to vehicle dynamics. The selected candidate will need to work in a physical vehicle and the CARLA simulator.
Note that this is a temporary position with a foreseen duration of 8 months.
HOSTING GROUP
The direct responsible persons for this post are Dr. Antonio M. López Peña and Dr. Gabriel Villalonga, members of the Autonomous Driving research group at the CVC.
The selected candidate is expected to participate in the following tasks:
- Autonomous Driving Research, in specific:
- Autonomous Driving models evaluation
- Implementation of Autonomous Driving methodologies in a real vehicle
CANDIDATE’S PROFILE
Please note that this role is intended for early-career. Applicants seeking internships or student placements will not be considered.
Required competences:
- C1-level English certification or equivalent
- Degree in Physics, Mathematics, or a closely related field
- Strong background in Deep Learning
- Proficiency in Python programming, particularly with PyTorch
Desirable (not mandatory) qualifications:
- Experience in academic research, including manuscript preparation and conference submissions
- Experience with the CARLA simulator
- Experience in Autonomous Driving research, particularly in:
- End-to-End Autonomous Driving (specifically CIL++)
- Diffusion models
- Physics-based (cinematic) vehicle models
- Fluency in Spanish
- Previous work or study experience in Europe (outside Spain) or the United States for at least three months
Applicants are expected to be fluent in both oral and written communication in English. They should work well in a multidisciplinary, team while demonstrating initiative, proactivity and independence.
CONTRACT CONDITIONS
- Location: Computer Vision Center (Campus Universitat Autònoma de Barcelona).
- Contract type: full-time (37.5h/week), temporary.
- Starting date: Immediate availability (mid-February 2026 / March 1st 2026)
- Duration: until October 31st 2026
- Salary: €22,500 annual gross, in accordance with the candidate’s qualifications, experience and CVC salary regulations.
APPLICATION PROCESS
All applications must be sent through the online form, indicating the offer code 20260202_ADLab and contain a full CV and contact details. Direct mails to the group members will not be answered.
The application process will remain open until February 12, 2026, 23:59 hours.
OTM-R principles for selection processes
The CVC is committed to Open Transparent and Merit-based Recruitment (OTM-R) for any potential candidate in all our processes. In 2015 we received the Human Resources Strategy for Researchers (HR Excellence in Research) award. Through an extensive and continuous process, we improve the conditions and opportunities at CVC. With these actions, the CVC is committed to the principles of the European Charter for Researchers, as well as the Code of Conduct for the Recruitment of Researchers. For more information follow this link.
References:
[1] Y. Xiao et al., Scaling Vision-based End-to-End Driving with Multi-View Attention Learning, IROS, 2023
[2] D. Porres et al., Guiding Attention in End-to-End Driving Models, IV 2024)








