Research Scientist in Visual Representation Learning (multiple positions) F/M

NAVER LABS Europe

Meylan

Sur place

EUR 40 000 - 70 000

Plein temps

14 jours+

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Avantages offerts par ce poste

Collaborative environment
Flexible work/life balance
Inclusive and diverse workplace

Résumé du poste

NAVER LABS Europe in Meylan is seeking two research scientists to join the Visual Representation Learning team. This opportunity involves working on innovative projects in visual perception for robots and autonomous platforms.

Candidates should possess a PhD in a relevant field, demonstrate research excellence, and have strong programming skills, particularly in Python and PyTorch. Join us in transforming research into impactful applications in AI.

Qualifications

  • PhD focus on visual representation learning, distillation, or generative modeling.
  • Track record of contributions to major conferences in computer vision and machine learning.
  • Ability to work collaboratively within a multidisciplinary team.
  • Excellent programming skills in Python and proficiency in PyTorch.
  • Experience with GPU computing and architectures.

Responsabilités

  • Join the VRL team focusing on pretraining visual encoders.
  • Contribute to projects in 3D scene reconstruction.
  • Collaborate closely within the team and across NAVER LABS.

Connaissances

Visual representation learning
Research excellence in computer vision
Programming skills in Python
Proficiency in PyTorch
Experience with GPU computing

Formation

PhD in computer science or related field

Description du poste

About NAVER LABS Europe

NAVER LABS Europe is part of the R&D division of NAVER, Korea’s leading Internet portal and a global tech company with a range of services that include search, commerce, content, fintech, robotics and cloud.


About The Team

The Visual Representation Learning (VRL) team works toward developing versatile representations to improve the visual perception modules of robots, self-driving vehicles and other autonomous platforms. Research also focuses on enhancing such perception modules with the ability to continuously learn as new environments or new interactions are observed. More information about our past research can be found on this page.


Our activities extend from theoretical contributions to practical, high-impact applications. We work closely within the team, across NAVER LABS Europe and with our colleagues from NAVER LABS in Korea. They are performed in tight collaboration within the team, across NAVER LABS Europe, and with our colleagues from NAVER LABS in Korea.


The Position

We are looking for two research scientists to join the VRL team on the projects described below (one position per project).



  • The first project focuses on pretraining strong and versatile visual encoders that can be directly applied to a large variety of tasks or adapted to new ones while mitigating catastrophic forgetting. These contributions are related to continual learning and knowledge distillation, and the person in this position will strengthen these lines of research.

  • The second project builds on recent in‑house contributions to 3D scene reconstruction (i.e. DUSt3R/MASt3R) and generative models. A proof of concept for small indoor rooms was recently created and this position would be focussed on scaling it.


Required Qualifications / What we’re looking for


  • A PhD in computer science, electrical engineering or a related field, with a focus on visual representation learning, including experience either in distillation, self‑supervised learning, generative modeling or 3D reconstruction.

  • A track record of research excellence, with contributions to major conferences and/or journals in computer vision (CVPR, ICCV, ECCV, PAMI) and machine learning (NeurIPS, ICML, ICLR, JMLR).

  • The ability to work collaboratively within a multidisciplinary team and to contribute to an inclusive team culture.

  • Excellent programming skills in Python and proficiency in PyTorch.

  • Experience with GPU computing and architectures.


Preferred Qualifications


  • A deep understanding and substantial experience in high‑performance computing would be a plus.

  • Some prior experience with multimodality would be of value.


Benefits / What we offer


  • We foster a collaborative environment dedicated to ambitious, multidisciplinary projects that translate advanced research into impactful, real‑world solutions, supported by 30+ years of experience in AI and related fields.

  • Flexible work/life balance.

  • We are an equal opportunity employer that hires based on skills, experience, and merit. We foster an inclusive and diverse workplace where all qualified candidates are considered fairly, regardless of background.

  • We’re based in Meylan, close to Grenoble, a city that offers the perfect balance of urban life, cutting‑edge research and technology, and spectacular mountain landscapes that provide countless opportunities to relax, recharge, and enjoy the outdoors.


All applications will be carefully considered, even if not all required skills are met. We value diverse backgrounds and the potential of each candidate, and we offer training to support the development of necessary skills.


NAVER LABS, co‑located in Korea and France, is the organization dedicated to preparing NAVER’s future. Scientists at NAVER LABS Europe are empowered to pursue long‑term research problems that, if successful, can have significant impact and transform NAVER. We take our ideas as far as research can to create the best technology of its kind. Active participation in the academic community and collaborations with world‑class public research groups are, among others, important ways to achieve these goals. Teamwork, focus and persistence are important values for us.


When applying for this position online, please don’t forget to upload your CV and cover letter. Incomplete applications will not be considered.


NAVER LABS Europe is subject to French jurisdiction requiring organisations to stipulate that a job/internship is open to both women and men. None of our jobs/internships are gender specific.


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