Open Positions

Post-doc


Title: Postdoc in 3D Computer Vision / Machine Learning
Location: Ecole Polytechnique, France
Start date: December 2021 - March 2022
Description:

A postdoctoral researcher position is available at the LIX research laboratory of Ecole Polytechnique in France, in the area of:

"Analyzing Large Scale 3D Shape Collections"

The goal of this project is to develop tools for the analysis of large-scale 3D shape collections, by designing novel Machine Learning techniques capable of processing and manipulating geometric data. The ultimate goal is to design tools for shape labeling, recognition, and matching across geometric data in 3D.

The ideal candidates should have strong background in at least some of the following:

- Computer Vision and Image Processing
- Machine Learning
- Programming experience, especially in multimedia data analysis
- Geometry Processing and 3D shape analysis

Candidates must have a PhD at the starting time of the post-doc, and should have publications in top venues in either Computer Vision (CVPR, ICCV, etc.) or Computer Graphics (e.g., SIGGRAPH, Eurographics, SGP). The expected duration of the post-doc is 2 years.

Venue and supervision:

Successful candidates will be based at Ecole Polytechnique located in Palaiseau, Paris area, France. The project will be supervised by Maks Ovsjanikov (LIX, Ecole Polytechnique).

How to apply:

To apply, please contact Maks Ovsjanikov (maks@lix.polytechnique.fr) and include [Computer Vision post-doc application] in the subject line. In your email, please include: 1) your CV with a publication list and 2) a short cover letter. In your cover letter, please make sure to explicitly describe your experience in the 4 topics mentioned above.

Reference letters are optional but may need to be provided upon request.

Post-doc


Title: Postdoc in 3D Geometry Processing / Computer Graphics
Location: Ecole Polytechnique, France
Start date: December 2021 - March 2022
Description:

A postdoctoral researcher position is available at the LIX research laboratory of Ecole Polytechnique in France, in the area of:

"Exploring Relations in Structured Data with Functional Maps"

The goal of this project is to develop tools for the analysis and processing of complex geometric data, such as large-scale 3D model collections, by building on techniques from Computer Graphics, Geometry Processing and Machine Learning. The ultimate objective is to create a unified framework for representing and analyzing structured data to solve problems such as: shape comparison and matching, shape segmentation and labeling, shape deformation and recognition among others. The project will be funded, in part, by the ERC Starting Grant EXPROTEA.

The ideal candidates should have strong background in at least some of the following:

- Geometry Processing and 3D shape analysis
- Computer Graphics
- Knowledge of Differential Geometry
- Numerical Optimization and Machine Learning
- Programming experience, especially in multimedia data analysis

Candidates must have a PhD at the starting time of the post-doc, and should have publications in top venues in either Computer Graphics or Geometry Processing (e.g., SIGGRAPH, Eurographics, SGP). The expected duration of the post-doc is 2 years.

Venue and supervision:

Successful candidates will be based at Ecole Polytechnique located in Palaiseau, Paris area, France. The project will be supervised by Maks Ovsjanikov (LIX, Ecole Polytechnique).

How to apply:

To apply, please contact Maks Ovsjanikov (maks@lix.polytechnique.fr) and include [Geometry Processing post-doc application] in the subject line. In your email, please include: 1) your CV with a publication list and 2) a short cover letter. In your cover letter, please make sure to explicitly describe your experience in the 5 topics mentioned above.

Reference letters are optional but may need to be provided upon request.

PhD student


Title: PhD student position in 3D Geometry Processing / Computer Graphics / Computer Vision
Location: Ecole Polytechnique, France
Start date: December 2021 - March 2022
Description:

One PhD student position is available at the LIX research laboratory of Ecole Polytechnique in France, in the area of:

"Exploring Relations in Structured Data with Functional Maps"

The goal of this project is to develop tools for the analysis and processing of complex geometric data, such as large-scale 3D model collections, by building on techniques from Computer Graphics, Geometry Processing and Machine Learning. The ultimate objective is to create a unified framework for representing and analyzing structured data to solve problems such as: shape comparison and matching, shape segmentation and labeling, shape deformation and recognition among others. The project will be funded, in part, by the ERC Starting Grant EXPROTEA.

The ideal candidates should have strong background in at least some of the following:

- Numerical optimization (e.g., continuous optimization with quasi-Newton methods, optimality conditions, constrained/unconstrained optimization, convex optimization, etc.)
- Numerical linear algebra (factorization methods for linear systems, sparse vs. dense systems, iterative vs. direct solvers, etc.)
- Differential Geometry (notions of Riemannian manifold, tangent space, vector fields, etc.)
- Fourier Analysis and spectral methods (Laplace operators on surfaces and graphs, heat equation, wave equation, etc.)
- Multimedia data analysis (images, 3D shapes, volumetric data) including learning-based techniques.
- Programming experience, especially in multimedia data analysis

For the PhD position, the candidate should have a Master's degree with preference given to those having strong research experience. The expected duration of the PhD is 3 years.

Venue and supervision:

Successful candidates will be based at Ecole Polytechnique located in Palaiseau, Paris area, France. The project will be supervised by Maks Ovsjanikov (LIX, Ecole Polytechnique).

How to apply:

To apply, please contact Maks Ovsjanikov (maks@lix.polytechnique.fr) and include [PhD application] in the subject line. In your email, please include: 1) Your CV, 2) Transcripts (list of courses taken with notes, for both Bachelor's and Master's-level courses), 3) Recommendation letters, if you have them, or, if not, contact information your previous teachers or supervisors that can provide feedback about your work, 4) A short cover letter. In your cover letter, please make sure to explicitly describe your experience in the 6 topics mentioned above.

Reference letters are optional but may need to be provided upon request.


Internships

Note: Unfortunately, I do not accept undergraduate internship requests. My only internship offers are for students currently enrolled in, or having completed their Master's degrees. I am sorry for not being able to respond to each individual undergraduate internship request.


Position: Research internship (Master's or PhD student)
Title: Deep Learning for 3D shape Matching
Location: Ecole Polytechnique, France
Start date: March — April 2020
Description:

The goal of this project is to develop a method for finding correspondences between non-rigid 3D models by using techniques from Machine Learning (Deep Learning in particular), Geometry Processing and Computer Graphics. Given a collection of 3D models, such as scans of humans in different poses, the goal is to learn effective ways for establishing point or region correspondences between new unseen pairs.

The ideal candidates should have strong background in at least some of the following:
- Numerical optimization and Numerical linear algebra
- Differential Geometry
- Fourier Analysis and spectral methods
- Machine Learning
- Programming experience, especially in multimedia data analysis (images, 3D shapes, volumetric data)

Strong preference will be given to candidates who wish to pursue a PhD at the end of the internship (starting in September 2020). The PhD has funding guaranteed by the ERC Starting Grant EXPROTEA.

Successful candidates will be based at Ecole Polytechnique located in Palaiseau, Paris area, France. The project will be supervised by Maks Ovsjanikov.

How to apply:
To apply, please contact Maks Ovsjanikov: maks@lix.polytechnique.fr, and put [internship application] in the subject line. In your email, please include your CV, the transcript of courses taken with the grades and a short cover letter. In your cover letter, please describe how your experience relates to the topics in this announcement.