MScT AI-ViC

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==== General Requirements ====

For first and second year, internship topics are to be validated by the academic co-directors of the MScT (Johannes Lutzeyer for the M1 and Xi Wang for the M2) by sending them an email mentioning the topic of the internship (with typically a half-page summary of the work to be done), the duration, the supervisor and the location of the internship. Once this is validated, please indicate Johannes (for M1 students) or Xi (for M2 students) as the "Enseignant référent" at Ecole Polytechnique on the official "convention de stage". During your internship defenses the 4 directors, including Aymeric Dieuleveut for M1 and Marie-Paule Cani for M2, will be involved as part of the jury.

**First-year Internship**

Period: from the beginning of April to the end of August (at least 4 months)

Defense: First half of September

An internship either in a private company or in a public lab. The research component of the internship is not mandatory but strongly encouraged. Students are requested to choose a topic related to the curriculum of their graduate degree program, i.e., involving either machine learning or visual computing, ideally both (see the first and second-year courses for details). This work can be theoretical (comprehension of a theorem and extension to a new setting), applied (developing and implementing a new solution), or a mix of theory and application.


**Second-year Internship**

Period: from the beginning of April to the end of September (at least 5 months)

Defense: First half of September (the internship can be continued after the defence)

A research internship either in the R&D department of a company or in a public research lab. The student must produce original work related to machine learning and/or to visual computing, ideally involving several different topics studied during the whole curriculum. This work can be theoretical or applied as soon as it contains novel ideas developed and validated by the student.


**Guidelines for the Report and the Examination Framework**

The report should be about 20 pages long, including figures and references. It must contain a general presentation of the topic and describe state-of-the-art methods in this field. The contributions of the student must be clearly identified and explained in details. There is no need for an exhaustive description of all codes produced during the internship. However, algorithms highlighting the challenging tasks solved by the student must be presented and explained in the report (if needed, relevant parts of the code can be included as well in an appendix). Below we provide some more detailed, section-by-section guidelines.

  * Introduction: motivation (why is your problem important, why is it challenging?), and a clear description of your goals;
  * Related work: Description of relevant former methods to solve the same or related problem, or methods your inspired from;
  * Proposed method (one or several sections): technical details about your scientific contributions and the solution your developed.
  * Experimental results and their validation, including discussion of pros and cons of your solution
  * Conclusions: What did you learn, ideas about future work...
  * References - please cite the journal/conference where the papers were published, if applicable, not the Axiv ref.

The oral examination will consist of a 15mn (sharp!) talk, on the same contents as the report. It will be followed by 10 minutes of questions and answers.


** 💡💡 Tips on how to find internships, provided directly by AI-ViC students, 2024-25 💡💡**

Thank you all for contributing to this useful feedback loop!

  * **Start very very early**, beginning of October preferably  
  * I handed out my CV at the fair and spoke for some time to the recruiter, and they contacted me later. Tips: Get as many details as you can about the company, projects and interview process at the fair, take notes, prepare accordingly and bring up the details you found interesting during the interviews.  
  * Talk to as many people as you can (reduce uncertainty and put yourself on the map)
  * To strengthen internship pipelines, we should tap into our alumni network and boost visibility between former interns and incoming students.   For instance, after my contribution at Amazon, my manager is eager to hire SDE interns straight from our university’s next cohort.  By organizing regular meet-and-greet sessions or panel discussions where recent graduates share their experiences with current students, we create direct referral channels and give hiring managers tangible reasons to scout talent from our program.
  * Use a centralised tracker such as [[https://github.com/henriChevreux/FR_jobspy.git]]
  * If you want to go to big tech, **apply on the first day** the opening opens.  Contact people from the company before applying. Check that the company / lab is a fit for you — not only that you are a fit for them.
  * Work on a niche project and reach out to people who would care about that niche.
  * Start as soon as possible.
  * Don't be afraid to reach out to people directly.
  * LinkedIn Outreach and Networking events
  * X-forum is a good chance -- If you try more, you have more -- Networking is all you need.

**<color #e32d2d> For M1 students: Access internship proposals from the Polytechnique engineering student page. </color>**

If you would like to see more internship proposals in Visual Computing, preselected for their decent research components, please follow this procedure:

  * Go there: https://stages.dix.polytechnique.fr/home
  * Register as student, with their email, and they can select the program "CSC_52994 - 2024" (Visual computing internships)
  * Then, Damien Rohmer will be able to validate your registration.
  * Once validated, they can connect with:
    * login: your email address
    * password: 3AstudentDIX

=============== Internship proposals 2025-2026 ===============================================
**<color #e32d2d>- Disney Research Summer Internship Program </color>**
  * Host: Disney Zurich, Switzerland

"Interns, assemble!" DisneyResearch|Studios and Disney Research Imagineering in Zurich, Switzerland, are looking for talented summer interns in computer graphics, machine learning, computer vision, and learning-based control. We are seeking candidates to solve new and emerging problems in visual effects, animation, and entertainment robotics. We are looking for individuals who share a passion for exploring complex, unsolved problems and are excited by the prospect of contributing to some of the most popular movie franchises of our time as well as the next generation of theme park experiences.

For 18 years, Disney Research has been at the forefront of technological innovation, pushing the boundaries of what is possible to help The Walt Disney Company differentiate its entertainment products, services, and content. Our mission is rooted in the long Disney tradition of inventing new technologies to contribute to the magic of the stories we tell and the characters we love. Our inventions are used in almost every Disney feature film production and have brought robotic characters to life that dazzle millions of guests worldwide.

Disney Research is part of a wider innovation ecosystem operating in close partnership with our technology units at the Walt Disney Animation Studios, Pixar Animation Studios, Lucasfilm/ILM, Marvel Studios, Walt Disney Pictures, 20th Century Studios, Searchlight, and Walt Disney Imagineering.

We offer an inspiring modern workplace close to the city center of Zurich, a collaborative work atmosphere, and exciting tasks in an international environment utilizing the latest technologies. Interns work under the supervision of our senior researchers. The summer internship will run for three months over June, July, and August in Zurich, though the exact dates are flexible. The working language is English.

Responsibilities
* Research, develop, and implement concepts, modules, or capabilities in image, video, geometry, motion processing, or robotics
*Collaborate with and support other engineers and researchers
*Communicate research project agendas, progress, and results

Minimum Qualifications:  Bachelor's or Master's degree in computer science (or related field), Currently enrolled as a university student (MSc or PhD level). Proven track record of achieving significant results

Preferred Qualifications
    *Demonstrated software engineering experience, coding competitions, or published papers
    *Experience with machine learning (particularly deep learning), rendering, computer vision, image processing, numerical optimization, animation technology, real-time game engines, or robotics
    *High level of creativity and quick problem-solving capabilities

To apply, please submit your resume and a cover letter that details your area of specialization and includes links to any representative papers. We will consider applications on a rolling basis, so apply early if possible.
[[https://studios.disneyresearch.com/internship-program/|Application link ]] 


**<color #e32d2d>- Identity Preserving image restoration </color>**
  * Host: DxO Labs
  * Keywords: Digital photography, image restoration, deblurring, sharpness enhancement, deep learning, generative models, diffusion models, personalized restoration, optimization.
  * Description:  [[https://www.dropbox.com/scl/fi/2oiwqr3oauivt6z0mvd9t/DxO-Identity-Preserving-Image-Restoration.pdf?rlkey=25jnl945qex8v3h175ftspvn1&st=2sr5xrkx&dl=0|link to the proposal]]


**<color #e32d2d> -  Development of Interactive Experiences in Virtual Reality for Immersive Art and Live Performances </color>**
  * Host: Vannes campus, EXPRESSION Team, IRISA Laboratory (Université Bretagne Sud).
  * Topic: exploring new forms of artistic expression through immersive technologies.
  * Objectives: The goal of the internship is to implement an application in a virtual environment to accompany an artistic installation composed of real objects. Within this application, sculptures, digital twins of physical sculptures, will evolve and allow users to interact with them. 
  * Keywords: 3D, simulation, art and science, multi-sensoriality, motion analysis, artificial intelligence, Unity 3D, VR/AR/XR
  * Profile: Master’s level (M2) computer science student or final-year engineering student (BAC+5 in progress), specializing in computer graphics, virtual reality, and/or artificial intelligence.
  * Practical: 6 months internship.
  * [[https://www.dropbox.com/scl/fi/ftjzxfgmatlmvmim005dw/ICCARE-internship-IRISA-Vannes-EV.pdf?rlkey=nr3tyldjyxeqshan05o1c4fl7&dl=0|link to the proposal]]


**<color #e32d2d> -  TRANSfer learning models able to handle MISSing data for the survival analysis of rare cancer from multi-OMICS data (CNRGH at Evry) </color>**
  * Host: Maths-Stats Team - National Center for Human Genome Research (CNRGH) at Evry.
  * Topic: Study models able to both deal with missing data and perform Transfer Learning to tackle the curse of dimensionality in cancer survival multi-omics studies.
  * Objectives: Perform a benchmark study of such methods on The Cancer Genome Atlas (TCGA); Eventually develop new statistical methods (mathematical optimisation).
  * Profile: M2 or last year of engineer school with specialty/knowledge in Computer Science / Statistics / Machine Learning / Deep Learning / BioStatistics. Working knowledge in programming (R / Python, ...). Previous experience with applications to genomics will be a plus.
  * Practical: 6 months internship.
  * [[https://www.dropbox.com/scl/fi/0fuhtmifyluqr8ahm1t6t/stageMaster_2026_CNRGH_CEA.pdf?rlkey=63yq5hy8pcz1zdklkkx49obm8&dl=0|link to the proposal]]

**<color #e32d2d> - Unified Vision Encoders: Multi-Teacher Distillation and Dynamic Transformers (valeo.ai) </color>**
  * Host: valeo.ai (Paris), research lab on ML & CV for automotive.
  * Topic: Distill multiple large vision encoders (e.g., Franca, SigLIP 2, VGGT) into one versatile transformer backbone.
  * Objectives: Design multi-teacher distillation pipelines for heterogeneous teachers; Develop dynamically scalable transformers (conditional depth / compute modes).
  * Profile: Final-year MSc (or equivalent) in ML / CV; Strong deep learning + PyTorch skills.
  * Practical: 6-month research internship (2025–2026), located in central Paris.
  * [[https://drive.google.com/file/d/1bYUb1l9C8b-Y8iGqpsBhrCLCk20du5X-/view?usp=sharing|link to the proposal]]

**<color #e32d2d> - Software Engineer en technologies web et IA (GE HealthCare) </color>**
The Software Engineer will join GE HealthCare's Advanced Visualization (AV) organization, dedicated to shaping the future of medical imaging through innovative web and AI technologies. This role offers the opportunity to integrate into a Scrum development team, focused on collaborative, cutting-edge projects like AI DREAM, which drives the creation of automated diagnostic and follow-up solutions. The engineer will contribute to the full-stack development of advanced components, critical functionalities in medical imagery, and define the architecture for algorithmic pipelines in computer vision. Ideal candidates possess proven expertise in computer vision, deep learning, client-server/web topologies, and proficiency in languages including TypeScript, CSS, HTML, and C++. [[https://drive.google.com/file/d/1hirsZOdS1iszWVMhJdG_ded2vpFvF6fS/view?usp=sharing|link to the proposal]]


**<color #e32d2d> - 2026 summer internships and Full-time positions in computational photography at Adobe </color>**
Colleagues, 
In my role as Vice President and Fellow at Adobe Inc., I run a team called Nextcam - a company-wide technology initiative focused on computational photography and AI at the point of capture, especially on mobile cameras.  We also work on AI-driven understanding and editing of still photographs and videos, and are keenly interested in how GenAI and large foundation models can help with these tasks.  As part of these efforts, my team is actively hiring.  In particular, we are looking for interns for Summer 2026, and full-time research scientists / research engineers - both junior and senior.

What has my team done recently?
Lots of stuff.  Most notably, we wrote and launched an experimental smartphone camera app called Indigo:
      https://research.adobe.com/articles/indigo/indigo.html
The app offers full manual controls, a more natural ("SLR-like") look, and the highest image quality that computational photography can provide - in both JPEG and raw formats.  It also introduces some new photographic experiences not available in other camera apps, such as removal of window reflections.  Indigo was released to the public in June 2025 as a free app on iPhone.  To our delight but not surprise, Indigo went viral, reaching 2 million downloads in the first few weeks, and received broad positive coverage in the tech press:
https://research.adobe.com/articles/indigo/indigo.html

https://www.theverge.com/news/690115/adobe-project-indigo-camera-app-marc-levoy

https://petapixel.com/2025/06/19/adobes-new-computational-iphone-camera-app-looks-incredible/

https://www.dpreview.com/news/4142720910/adobe-quietly-made-a-super-powered-camera-app-for-iphone

https://gregbenzphotography.com/photography-reviews/project-indigo-the-best-camera-app-for-smart-phones/

In addition to Indigo, my team develops computational and learning-based technologies that go into multiple Adobe products.  For example, in 2024 we launched Adobe Adaptive Profile, which uses AI to adjust the color and tone of your photographs based on a semantic analysis of scene content:
     https://blog.adobe.com/en/publish/2024/10/14/the-adobe-adaptive-profile
and in early 2025 we launched an AI-based technology for removing window reflections from photographs:
     https://blog.adobe.com/en/publish/2024/12/12/removing-window-reflections-adobe-camera-raw
Both technologies run in Adobe Camera Raw and Lightroom, and have tens of millions of users.

Are we a research team, or a product team?
In a word - both.  My team collaborates closely with Adobe Research, but is separate from it.  We have more the feeling of a small startup inside a big company, but a startup with the resources of a successful tech company. Here are some of the people on my team, and examples of their recent research:

Here are some of the people on my team, and examples of their recent research:

Florian Kainz:       https://blog.adobe.com/en/publish/2024/10/14/the-adobe-adaptive-profile

Eric Kee:                https://erickee.com/reflections/cvpr2025.html

Zhoutong Zhang: https://ztzhang.info/

Shumian Xin:        https://shumianxin.github.io

Yuting Yang:         https://yyuting.github.io

Ruiming Cao:       https://rmcao.net

Ilya Chugunov:     https://ilyac.info

Mingdeng Cao:    https://scholar.google.com/citations?user=EcS0L5sAAAAJ&hl=en

Zeqi Gu:                https://www.cs.cornell.edu/~zeqigu/

and here are some papers we've published recently, many of them with past interns: 
- Learning to Refocus with Video Diffusion Model, Siggraph Asia 2025, SaiKiran Tedla, Zhoutong Zhang, Xuaner Zhang, Shumian Xin.
- LEDiff: Latent Exposure Diffusion for HDR Generation, CVPR 2025, Chao Wang, Zhihao Xia, Thomas Leimkuhler, Karol Myszkowski, Xuaner Zhang.
- Classic Video Denoising in a Machine Learning World: Robust, Fast, and Controllable, CVPR 2025, Xin Jin, Simon Niklaus, Zhoutong Zhang, Zhihao Xia, Chunle Guo, Yuting Yang, Jiawen Chen, Chong-Yi Li.
- Instruction-based image manipulation by watching how things move, CVPR 2025. Mingdeng Cao, Xuaner Zhang, Yinqiang Zheng, Zhihao Xia. 
- Removing Reflections from RAW Photos, CVPR 2025. Eric Kee, Adam Pikielny, Kevin Blackburn-Matzen, Marc Levoy.
- Restoration by Generation with Constrained Priors, CVPR 2024, Zheng Ding, Xuaner Zhang, Zhuowen Tu, Zhihao Xia.
- Explorative Inbetweening of Time and Space, ECCV 2024, Haiwen Feng, Zheng Ding, Zhihao Xia, Simon Niklaus, Victoria Abrevaya, Michael J. Black, Xuaner Zhang.
- Fast View Synthesis of Casual Videos with Soup-of-Planes, ECCV 2024, Yao-Chih Lee, Zhoutong Zhang, Kevin Blackburn-Matzen, Simon Niklaus, Jianming Zhang, Jia-Bin Huang, Feng Liu.
- Self-Supervised Burst Super-Resolution, ICCV 2023, Goutam Bhat, Michaël Gharbi, Jiawen Chen, Luc Van Gool, Zhihao Xia.
- DiffusionRig: Learning Personalized Priors for Facial Appearance Editing, CVPR 2023, Zheng Ding, Xuaner Zhang, Zhihao Xia, Lars Jebe, Zhuowen Tu, Xiuming Zhang.
- SunStage: Portrait Reconstruction and Relighting using the Sun as a Light Stage, CVPR 2023, Yifan Wang, Aleksander Holynski, Xiuming Zhang, Xuaner Zhang.
- Automatic High Resolution Wire Segmentation and Removal, CVPR 2023, Mang Tik Chiu, Xuaner Zhang, Zijun Wei, Yuqian Zhou, Eli Shechtman, Connelly Barnes, Zhe Lin, Florian Kainz, Sohrab Amirghodsi, Humphrey Shi.
- Neural Photo-Finishing, SIGGRAPH Asia 2022, Ethan Tseng, Yuxuan Zhang, Lars Jebe, Xuaner Zhang, Zhihao Xia, Yifei Fan, Felix Heide, Jiawen Chen,
- The Implicit Values of A Good Hand Shake: Handheld Multi-Frame Neural Depth Refinement, CVPR 2022, Ilya Chugunov, Yuxuan Zhang, Zhihao Xia, Xuaner Zhang, Jiawen Chen, Felix Heide

What sort of people are we looking for?

Internships:

Preferred candidates for internships are current MS or PhD students with training in computer graphics, computer vision, computational photography, or machine learning.  Interns will be encouraged to pursue research and to publish, and should be interested in steering their research towards productization, so that Adobe can eventually ship their technologies in software products, with broad impact on imaging, photography, and the camera industry.  Interns will not be expected to write production code.


Interested in an internship?  Here is a link to Adobe's official job description: https://research.adobe.com/careers/internships/ 

Students may also contact my team directly via this email address:mailto:nextcam-internships@adobe.com 

Offers are made on a rolling basis, and priority is given to candidates who apply before January 1, 2026.  These internships will be local in San Jose, although exceptions are possible in rare cases, e.g. if the mentor is themselves remote.

Full-time positions:
Preferred candidates for full-time positions should be newly or recently graduated MS or PhD students, or experienced researchers / engineers in existing companies, again with training in computer graphics, computer vision, computational photography, or machine learning.  Research scientists / engineers are welcome to publish, but should also be interested in rolling up their sleeves and shipping their technologies.  We collaborate closely with teams elsewhere in Adobe that can help with productization.

Interested in a full-time position?  We're actually looking for both research scientists and ML engineers, with slightly different roles and requirements. Here are links to Adobe's official job descriptions for both kinds of jobs:

https://www.linkedin.com/jobs/view/computer-scientist-at-adobe-4312887392/?skipRedirect=true&utm_source=chatgpt.com

https://www.linkedin.com/jobs/view/ai-software-development-engineer-at-adobe-4313121358/?skipRedirect=true&utm_source=chatgpt.com

Students may also contact my team directly via this email address:mailto:nextcam-jobs@adobe.com 

So please let your students know we are hiring!
And please ask them to specify which position they are interested in.
-Marc Levoy
 Vice President and Fellow
 Adobe Inc.

**<color #e32d2d> - M2 research internship at LIRIS, Lyon, leading to a funded PhD </color>**
Hello,
As part of the ANR BIM-4-SIM project, which focuses on "Generation and modeling of urban buildings for thermal and energy simulations," we are offering a Master's level (M2) internship in the automated generation of building interiors and exteriors.

The full project description is available here: [[https://liris.cnrs.fr/emploi/generation-automatique-batiments-3d-interieurs-et-exterieurs | link to proposal]]. 

This internship may lead to a PhD, as funding is already secured within the ANR project.
Contacts:
guillaume.damiand@cnrs.fr
adrien.peytavie@univ-lyon1.fr


**<color #e32d2d> - Research internship at Inria specifically sent for AI-ViC/ViCAI students </color>**

* Location: Inria Sophia Antipolis
  * Contact: Guillaume Cordonnier <Guillaume.Cordonnier@inria.fr>
  * Topic 1: Stochastic Flow Paths for Fast Hazard Simulation [[https://drive.google.com/file/d/1GByd0GyQUR4mt6xwZOLK2-iasyjg4Xgk/view?usp=sharing|link to the proposal]]
  * Topic 2: Modeling the present, past and future of real terrains from in-situ geological annotations [[https://drive.google.com/file/d/1BM3pGBJ32emQsSpejoF39aJ2HldhQDUQ/view?usp=sharing|link to the proposal]] (Could be extended to a Ph.D.)

* Location: Inria Sophia Antipolis
  * Duration: 6 months
  * Contact: Adrien Bousseau <adrien.bousseau@inria.fr>
  * Topic 1: Reusing decommissioned curved objects to create new surfaces[[https://www-sop.inria.fr/members/Adrien.Bousseau/stages/BladeReuse.pdf|link to the proposal]]
  * Topic 2 (Master2 preferred): Layer-Based Garment Modeling for Textile Form Weaving [[https://www-sop.inria.fr/members/Adrien.Bousseau/stages/FormWeavingInternship.pdf|link to the proposal]]



**<color #e32d2d> - Mistral AI  - Internship Master/PhD/CIFRE </color>**
 
Become a part of a pioneering company shaping the future of AI!

Background: currently doing a Master in IA/Data Science or PhD from tier 1 engineering schools/Universities.
Totally Open for CIFRE Programs. High scientific understanding of the field of generative AI.
Familiarity with natural language processing techniques and machine learning algorithms.
Expert with Python/PyTorch.

Location :  Paris/London/Palo Alto.
Starting: ASAP.

►About Mistral AI

Mistral AI is a pioneering French artificial intelligence startup founded in April 2023 by Arthur Mensch, Guillaume Lample and Timothée Lacroix.
United by their shared academic roots at École Polytechnique and experiences at Google DeepMind and Meta, they envisioned a different, audacious approach to artificial intelligence to challenge the opaque-box nature of ‘big AI’, and making this cutting-edge technology accessible to all. Mistral AI's comprehensive AI platform is designed to meet enterprise needs whether on-premices or in cloud environments.
Their offerings include le Chat, the AI assistant for life and work
Mistral AI raised a total of 1.7B€ in its latest founding round to accelerate technological progress with AI 

►Mistral AI is currently looking for:

Internship - Master/CIFRE - AI Scientist (Paris) : https://dl6s4.r.ah.d.sendibm5.com/mk/cl/f/sh/1t6Af4OiGsHKgS5a7ZOW8ARczjo5hP/pYTQ9O6mnj4o

Internship - Master/PhD - CIFRE Applied AI, Forward Deployed Machine Learning Engineer (Paris): https://dl6s4.r.ah.d.sendibm5.com/mk/cl/f/sh/1t6Af4OiGsHn1AI0VvURIQVSNYmpPT/CqzqLruR9EZx

Internship - Master/PhD Applied Scientist/Research Engineer (Paris/London) : https://dl6s4.r.ah.d.sendibm5.com/mk/cl/f/sh/7nVU1aA2nfsZpYruuryIkUExl0hk3yZ/RR7lNfNL8sOs
    

**<color #e32d2d> Visual Recognition Group (CTU), VISTA (École Polytechnique), Imagine (École des Ponts) (M1 or M2) </color>**
  * Locations: Paris (France) or Prague (Czech Republic)
  * Duration: 4–6 months
  * Requirements: any MSc levels, see each topic.

  * A Generative Approach to Global Visual Geolocation: The Use of Image Retrieval and Nearest Neighbors [[https://drive.google.com/file/d/1KyxT4qMfv9tD7PUUqCmNj_OEEVyku_RG/view?usp=sharing|link to the proposal]]
  * Attacking Google Image Search [[https://drive.google.com/file/d/1D8nY4in7-OLF2V_nU3xL6MCP8SSbCroO/view?usp=sharing|link to the proposal]]
  * Interpretable Image-to-Image Similarity with Deep Models [[https://drive.google.com/file/d/1h4qfvTEP7y3bEuaJE6aB9XMdLpMpQjC-/view?usp=sharing|link to the proposal]]
  * Deep Ensembles for Image-to-Image Similarity with Local Descriptors [[https://drive.google.com/file/d/19sfeH6txFKURLjXawoYkijPrjcTyxYJk/view?usp=sharing|link to the proposal]]
  * Training Visual Search Models for Conflicting Logo Identification via Personalized Generative Data [[https://drive.google.com/file/d/1zv06Jw4j9AdmK-X28eBuqgxBfptaimUw/view?usp=sharing|link to the proposal]]
  * Open-Vocabulary Zero-Shot Co-Segmentation with Vision-Language Models [[https://drive.google.com/file/d/18mflqhnZFkbC2dx-NqGYAoZ2iCIEaT7e/view?usp=sharing|link to the proposal]]
  * Exploring Memorization in Generative Models via Large-Scale Image Retrieval [[https://drive.google.com/file/d/18U-WhQFV7nfeAhD1NaMaBucgdEsh-yrC/view?usp=sharing|link to the proposal]]



**<color #e32d2d> Research in Graph-Machine Learning applied to logistic </color>**

**Location:** full-remote

**Contact:** theophile@monoceros-sas.fr

**Duration:** 4 to 6 months, depending on the student’s availability

**Organisations:** Monoceros SAS, Unicef

**Project Objectives:** Optimization of UNICEF's Supply Chain in Madagascar with data collected by the Monoceros SmartM system and modelled using Graph-Machine Learning algorithms. This project aims to explore and exploit graph-oriented database technologies (Graph-DB) and Graph- Machine Learning (Graph-ML) algorithms to optimize logistics and strengthen the resilience of UNICEF's supply chain in Madagascar.

[[https://www.dropbox.com/scl/fi/zytyawg7yc6x6eyvztbp3/Stage-Data-Science-EN.pdf?rlkey=ja38w6lt3n69g6eki0757i12i&dl=0|link to the proposal]]








=============== Internship proposals 2024-2025 ===============================================

**<color #e32d2d> CALYPSO project, Lille University (M2) </color>** 
Master internship in AI and Computer vision applied to neurosciences and phycological disorders: [[https://www.dropbox.com/scl/fi/gl8wot5zs5f6tthuf2a74/Offre-de-stage-M2-Projet-CALYPSO.pdf?rlkey=70bnmeq3ke0dcp87icx2ryz2x&dl=0|link to the proposal]]

**<color #e32d2d> Thales & LIP6 Sorbonne Université (M2, possibility to pursue with a PhD.) </color>** 
Master internship in Data Visualization applied to Trustworthy AI of critical systems: [[https://julien-tierny.github.io/stuff/openPositions/internship2025b.pdf|link to the proposal]]

**<color #e32d2d> LIP6 Sorbonne Université & CEA (M2, possibility to pursue with a PhD.) </color>** 
Master internship in Data Visualization: [[https://julien-tierny.github.io/stuff/openPositions/internship2025a.pdf|link to the proposal]]


**<color #e32d2d> Ideactiv (M2, french speaker preferred, possibility to pursue with a PhD.) </color>** 
Master internships in Natural Language Processing applied to Culture. 
See the announcement here: [[https://www.dropbox.com/scl/fi/4ibiuw55iug9if0h952cq/ideactiv.-Stage-IA-ML-NLP.-Dec-24.pdf?rlkey=7a8p4nb096hjup7t1ptecjlk9&dl=0|link to the proposals]]

**<color #e32d2d> LASTIG lab (M2) [[https://www.umr-lastig.fr/]] (M2) </color>** Master internship in the visualization of Urban multi-modal data from the GEOVIS team (Visualization, Interaction and Immersion) - Visual computing topic (no AI): [[ https://www.umr-lastig.fr/lastig_data/pdf/2025_stage_geovis_mobidec.pdf|link to the proposal]]

**<color #e32d2d> GE Healthcare France (M1 or M2) </color>** [[https://www.dropbox.com/scl/fi/nanp05g50m1o1ugjo0iy6/OffresGeneriques_GE_HealthCare.pdf?rlkey=k8eyk6xa18516zbnh43g6hoqs&dl=0|link to the proposals]]
  * Topics
    *  Artificial Intelligence for health
    *  Image processing and applied math
  * Contact Vincent Jugnon <vincent.jugnon@gehealthcare.com>

**<color #e32d2d> Dassault systems (M2 only) </color>** [[https://www.3ds.com/careers/jobs/stage-data-scientist-3d-generatif-junior-h-f-540544|link to the proposals]]
  * Topics
    * Generative AI applied to 3D prototyping  
  * Contact Nathan Pollet <Nathan.POLLET@3ds.com>

**<color #e32d2d> Adobe - internships in computational photography in San Jose, USA </color>** 
-------- Forwarded Message --------
Subject: 	Summer 2025 internships in computational photography at Adobe
Date: 	Fri, 8 Nov 2024 01:52:55 +0000
From: 	Marc Levoy 

Colleagues,
In my role as Vice President and Fellow at Adobe Inc, I am spearheading a company-wide technology initiative focused on computational photography and video.  Among other projects, we are building a camera app for smartphones with world-class image quality and magical super-powers, and we are developing computational and learning-based technologies that will go into multiple Adobe products. We're particularly interested in the application of GenAI to photographic problems.  As examples of recent learning-based technologies we've explored, you may have seen our MAX 2023 Sneak Peek on removing window reflections: https://youtu.be/hjLcIc7-bF4 , or the launch at MAX 2024 of Adobe Adaptive Profile, which uses AI to adjust the color and tone of your photographs based on a semantic analysis of scene content: https://blog.adobe.com/en/publish/2024/10/14/the-adobe-adaptive-profile . The Adaptive Profile notably produces HDR results from DNGs (or other raw format files). For SLR/MIR camera users, this may be the first time they've seen their photographs rendered in high dynamic range.

As part of projects like this, my team is looking to hire interns for Summer 2025.
Preferred candidates for internships are current MS or PhD students with training in computer graphics, computer vision, computational photography, or machine learning.
 
Interns will be encouraged to pursue research and to publish, and should be interested in steering their research towards productization, so that Adobe can eventually ship their technologies in software products, with broad impact on imaging, photography, and the camera industry.  Interns will not be expected to write production code. My team collaborates closely with Adobe Research, but is separate from it.  

Interested?  Here is a link to Adobe's official job description: https://research.adobe.com/careers/internships/ 
Students may also contact my team directly via this email address: nextcam-internships@adobe.com 

Offers are made on a rolling basis, and priority is given to candidates who apply
before December 1, 2024.  These internships will be local in San Jose, although
exceptions are possible in rare cases, e.g. if the mentor is themselves remote.
So please let your students know we are hiring!
-Marc Levoy
 Vice President and Fellow
 Adobe Inc.

**<color #e32d2d> DeepMind - Call for Student Researchers at Google DeepMind </color>** 
-------- Note: they ask for PhD students coming for internships; no guarantees that M2 master students are accepted but you could try --------
From David Salesin:

At Google DeepMind, Miki Rubinstein and I are leading a talented team of researchers and engineers working at the forefront of generative AI, computer vision, and graphics. Our team is known for pursuing research that pushes the boundaries of what is possible (e.g., Generative Image Dynamics, W.A.L.T, Lumiere, VideoPoet, Muse, DreamBooth, DreamFusion, NeRF); making direct contributions to Google’s foundation models (Imagen, Veo, Gemini); and turning our world-class research into product features with literally billions of users (e.g., Cinematic Moments for Photos, Cinematic Wallpaper for Android, Best Take for Pixel, Immersive View for Maps, Dream Screen for YouTube, AI Image Generator for Cloud, and Product Studio for Shopping).

We are looking to hire PhD students in computer vision, graphics, and machine learning to join us as Student Researchers to advance the state of the art in these areas. We publish in top-tier venues like CVPR, SIGGRAPH, NeurIPS and ICML.

Our team includes 60+ people (including those listed below) and spans numerous locations:

    San Francisco (myself, Jon Barron, Pratul Srinivasan, Aleksander Hołyński, Songyou Peng, Janne Kontkanen, Dor Verbin, Albert Shaw, Glenn Entis);
    Atlanta (Thad Starner, Irfan Essa, José Lezama, Grant Schindler, Meera Hahn);
    Cambridge, Mass (Bill Freeman, Deqing Sun, Miki Rubinstein, Forrester Cole, Charles Herrmann, Junhwa Hur, Lijie Fan, Erika Lu, Sarah Rumbley);
    Mountain View (Leonidas Guibas, Tom Funkhouser, Madison Le, Siddhant Jain);
    New York City (Noah Snavely, Ramin Zabih, Richard Tucker, Kyle Genova);
    Tel Aviv (Tali Dekel, Inbar Mosseri, Roni Paiss);
    Seattle (Rick Szeliski, Brian Curless, Amit Raj);
    Berlin (Daniel Sýkora);
    London (Peter Hedman);
    Zurich (Stefan Popov);
    Playa Vista (James Vecore).

We hope you will join us! Here’s how to apply:
    Submit a formal application: US, Israel, Europe (note the December 13 deadline for Israel and Europe!)
    Please email gdm-ct-internships@google.com to let us know you applied. Include your CV, and any other relevant info—for example, with whom you’d like to work.
We will be considering applications on a rolling basis, so please apply as early as possible. Thanks!

**<color #e32d2d> Artefact - Deep learning, Computer Vision - 19 rue Richer, 75009, Paris, www.artefact.com        </color>** 
 * Topics
    *  Deep learning and operational research for Supermarkets [[https://www.dropbox.com/scl/fi/t8lj4qwiczx7050hbzgri/2025_Fiche-de-poste-stage-Assort.pdf?rlkey=z4uygwzcpe12x38fgce15pp9h&dl=0]]
    *  Tree-based scoring method [[https://www.dropbox.com/scl/fi/8mh033i9xf153t3kcfmrp/2025_Fiche-de-poste-stage-ARC-Tree.pdf?rlkey=t98me887vljcq9f5z8ydbiyz4&dl=0]]


**<color #e32d2d> Laboratoire I3S (CNRS UniCA) Equipe Mediacoding - Sophia Antipolis       </color>** 
  Topic: 3D ADN: [[https://webusers.i3s.unice.fr/~fpayan/data/offres/Internship_Topic_I3S_Payan_24-25_en-fr.pdf]]
  Contacts : Frédéric Payan - fpayan@i3s.unice.fr ; Marc Antonini - am@i3s.unice.fr
  
  
**<color #e32d2d> Seelab - Hybrid (remote + on-site in Paris or Nantes)       </color>**  

Topic and Company Presentation: [[https://www.dropbox.com/scl/fo/2ql7brndzh7ukpkkgbiw0/AAwr-5fRpA3vrB9kWfT4ieE?rlkey=rd49b3jdmcbnrv7bydc87lscm&dl=0]]
  
Dans le cadre de nos projets de recherche et développement chez Seelab.ai, nous recherchons un(e) stagiaire en cycle master ou post doctorant pour travailler sur des problématiques avancées en computer vision.

Le stage que nous proposons portera notamment sur de la recherche et du fine-tuning de modèles de diffusion axés sur la génération et le traitement d’images, impliquant l’optimisation de pipelines existants, l’adaptation de modèles via LoRA et ControlNet. 
  
  Contacts : Ronan Tessier - ronan@seelab.ai 


=============== Internship proposals 2022-2023 =======================
This list is kept here as inspirations/ideas on companies your could contact to find an internship.

** <color #22b14c> Decathlon SportsLab at Lille (France) - Research Internship in Computer Vision "Strategy for the integration of Visual Computing for the analysis of sports movement and posture”</color>**

Link internship offers: http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=2023_02_27_training_offer-decathlon-visual_computing_lille.pdf

Duration:The 5 to 6-month internship 

Périod: start on april 2023

How to apply? Send by mail your Corver letter, Resume (more information online)

Contact to apply: 
GUILLAUME DIVRECHY <guillaume.divrechy@decathlon.com>
Human Factors & Ergonomics Lab, team player
SportsLab Quality Assurance, project leader 2023

** <color #22b14c> ASSYSTEM Paris La Défense/Courbevoie (France), in the DataScience team within the ASSYSTEM Digital Factory (group of 70 people) in La Défense, for M1 or M2 students </color>**

Links internship offers : 

1) Contribution to the product roadmap of an AI solution "eMoby" for CV analysis and matching with job descriptions
http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=2023_02_09_internship_emoby_cv_parsing_fr_assystem.pdf

2) Contribution to assystem's innovation programme concerning the application of AI algorithms in engineering processes related to the energy transition
http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=2023_02_09_internship_digital_engineering_fr_assystem.pdf

Duration : 6 months. The intern will work on the Assystem site in Paris La Défense/Courbevoie. Homeworkin possible.

Périod : march 2023

Website: www.assystem.com

How to apply? Send by mail your Corver letter, Resume (more information online) 

Contact to apply: jobs.assystem.com

** <color #22b14c> ARTEFACT Paris - Research Internship in Computer Vision “Scalable Multi Objects Tracking for Retail”</color>**

Link internship offers : http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=20230126_computer_vision_research_internship_-_computer_vision_research_internship_1_.pdf

Duration : The 5 to 6-month internship 
Périod : march 2023
Website: https://www.artefact.com/

How to apply? Send by mail your Corver letter, Resume (more information online)

Contact to apply: please write an e-mail to charlotte.silo@artefact.com and emmanuel.malherbe@artefact.com


** <color #22b14c> GLEAMER - 117 Quai de Valmy - 75010 Paris - AI engineer trainee</color>**

The AI engineer trainee will help us improve our deep learning models on 2D and/or 3D medical images and then join us on a permanent basis.

Link internship offers for M2 in FR & GB : http://bit.ly/3XXyW6M

Duration : The 6-month internship and contract CDI after
Périod : start march 2023
Website:  https://www.gleamer.ai/

How to apply? Send by mail your Corver letter, Resume (more information online)

Contact to apply: 
Misrachi Gabriel 
AI Engineer
Gabriel Misrachi <gabriel.misrachi@gleamer.ai>


** <color #22b14c> Inria Rennes (www.inria.fr/centre/rennes), Campus Universitaire de Beaulieu, on the team MimeTIC (www.irisa.fr/mimetic/) - M2 internship offer on synchronisation between real and virtual cyclists in augmented reality </color>**

Link internship offers for M2 in FR & GB : 
http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=20221213_stage_sharespace_fr.pdf

http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=20121213_internship_sharespace_en.pdf

Duration : The 6-month internship 
Périod : betwen middle of -january and middle of July 2023 (<color #ed1c24>**WARNING**:</color>for MScT AI-ViC - departure on internship after courses and examination on march, perhaps negociate April to august or september)
Website:  

How to apply? Send by mail your Corver letter, Resume (more information online)

Contact to apply: 
Richard Kulpa
Maître de conférences
Laboratoire M2S - Inria MimeTIC        
m2slab.com
Richard Kulpa <richard.kulpa@irisa.fr>

Co-porteur de l'EUR DIGISPORT
digisport.univ-rennes.fr
Newsletter DIGISPORT
 




** <color #22b14c>ideactiv – essentiellement en télétravail, avec des points de rendez-vous réguliers en ligne et en présentiel avec le fondateur d’ideactiv (X93) (Fr) - M2 internship: IA / machine learning
Amélioration des performances d’un “deep search engine” </color>**

Link internship offers for M2 in FR & GB : 
http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=2022_11_30_internship_offer_ideactiv._stage_ai_ml._nov_22._en.pdf

http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=20221130_offre_stage_ideactiv._stage_ia_ml._nov_22._fr.pdf

http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=2022_11_30_ideactiv_-_sujets_de_stage_ai_ml_-_nov_22.pdf


Duration : The 6-month internship will start in early 2023, with a possibility to start a Ph.D or hiring

Website:  https://www.ideactiv.com/index.php?public=

How to apply? Send by mail your Corver letter, Resume (more information online)

Contact to apply: 
Thomas Chenevier
hello@ideactiv.com


** <color #22b14c>INRIA – Grenoble (Fr) - M2 internship: Video-based dynamic garment representation and synthesis </color>**

Link internship offers for M2 :  https://team.inria.fr/morpheo/category/job-offers/

Duration : The 6-month internship will start in early 2023, with a possibility to start a Ph.D. in October 2023  (for a duration of 3 years). The Ph.D. will be supervised by Pierre Héllier (Interdigital Rennes), Bharath Damodaran (Interdigital Rennes), Adnane Boukhayma (Inria Rennes), and Stefanie Wuhrer (Inria Grenoble).

How to apply? Send by mail your Corver letter, Resume and transcript of grades (more information online)

Contact to apply: Stefanie Wuhrer <stefanie.wuhrer@inria.fr>


** <color #22b14c>PRIMAA – Paris (Fr) </color>**

Link internship offers : 

1) Applications of unsupervised learning in histopathology
[[https://www.welcometothejungle.com/fr/companies/primaa/jobs/intership-applications-of-unsupervised-learning-in-histopathology_paris]] 

2) Weakly Supervised learning for histopathology
[[https://www.welcometothejungle.com/en/companies/primaa/jobs/internship-weakly-supervised-learning-for-histopathology_paris]] 

How to apply? Send by mail your Corver letter and Resume and/or on line

Contact to apply: 
M. Adrien Nivaggioli (MScT AI-ViC alumni)
adrien@primaalab.com 




** <color #22b14c>Worldline – Human / bot behavior identification – Lyon (Fr) </color>**

Link internship offers : https://jobs.worldline.com/Worldline/job/Lyon-69-STAGE-IA-ANALYSE-DE-DONNEES-DE-PAIEMENT-AVEC-DU-MACHINE-LEARNING-%28HF%29-1-1-Rh%C3%B4n/756908202/

Good level in English requiered

How to apply? Send by mail your Corver letter and resume and/or on line

Contacts to apply: 
MENARD, SAMUEL <samuel.menard@worldline.com>
R&D Engineer
Worldline Labs – AI Skill Center
Tel +33 (0)4 78 17 80 93
53, avenue Paul Krüger
69624 Villeurbanne Cedex - France



Human / bot behavior identification

** <color #22b14c>Inria – Rationalization of CAD assemblies – Sophia-Antipolis (Fr-near Nice) ; Master-level internship, could be extended to a PhD </color>**

Link internship offers : http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=20221019_internship_offer_inria_sophia_cadassembly.pdf

Internship bonus : The internship will take place at Inria Sophia Antipolis. Inria will provide a monthly stipend
of around 1100 euros for EU citizens in their final year of masters, and 400 euros for other
candidates. Candidates should have strong programming and mathematical skills as well as
knowledge in computer graphics, geometry processing and optimization

How to apply? Send by mail your Corver letter and resume

Contacts to apply: 
Adrien Bousseau and Florent Lafarge, Inria Sophia Antipolis
adrien.bousseau@inria.fr
florent.lafarge@inria.fr
http://www-sop.inria.fr/members/Adrien.Bousseau/
http://www-sop.inria.fr/members/Florent.Lafarge/


** <color #22b14c>Inria – Utilisation de deep learning pour le changement d’échelle des données satellites
d’observation de la Terre – LERMA de l’observatoire de Paris (Fr)</color>**

Link internship offers :
http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=20221014_internship_downscaling_observatoire.pdf

How to apply? Send by mail your Corver letter and resume

Contacts to apply: 
Laboratory: LERMA, Observatoire de Paris, 61 avenue de l’Observatoire 75014 Paris
Supervisor: Filipe AIRES, filipe.aires@obspm.fr, 06 20 15 22 98
Requested background: Strong background in applied mathematics/physics. Good programming



** <color #22b14c>Inria – Subcell erosion for terrain generation – Sophia-Antipolis (Fr-near Nice) </color>**

Link internship offers :http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=20221011_internship_subcellerosion_inria.pdf

Internship bonus : Inria will provide a monthly stipend of around 1100 euros for EU citizens in their final year of masters, and ~600 euros for other candidates.

How to apply? Send by mail your Corver letter and resume

Contacts to apply: 
Guillaume Cordonnier, GRAPHDECO, Inria Sophia Antipolis (France)
http://team.inria.fr/graphdeco
Guillaume.Cordonnier@inria.fr
http://www-sop.inria.fr/members/Guillaume.Cordonnier/


** <color #22b14c>Inria – Instant generation of geomorphologically accurate terrain – Sophia-Antipolis (Fr-near Nice) </color>**

Link internship offers :http://www.lix.polytechnique.fr/Labo/Marie-Paule.Cani/MasterAI/lib/exe/fetch.php?media=20221011_internship_fastterrains_inria.pdf

Internship bonus : Inria will provide a monthly stipend of around 1100 euros for EU citizens in their final year of masters, and ~600 euros for other candidates.

How to apply? Send by mail your Corver letter and resume

Contacts to apply: 
Guillaume Cordonnier, GRAPHDECO, Inria Sophia Antipolis (France)
http://team.inria.fr/graphdeco
Guillaume.Cordonnier@inria.fr
http://www-sop.inria.fr/members/Guillaume.Cordonnier/illaume.Cordonnier/




====== PhD thesis proposals =======


**THALES**


**Automatiser une chaine de renseignement militaire** (THALES, apprenti ou thèse sur 3 ans). 

L’observation est permanente. On traite plus de 10 000 interceptions par jour soit plusieurs dizaines ou centaines de millions d’impulsions radar élémentaires. Le traitement est automatique mais il peut y avoir par exemple 1% d’échec ce qui représente entre 100 ou 1000 interceptions ou plus. Le traitement fait un diagnostic de chaque interception sur chaque paramètre pour savoir si il y a correspondance avec un signal cible. Le traitement analyse pour cela plus de 100 paramètres, avec une hiérarchie sur les types d’erreur rencontrés. Il peut être aussi amené à déclencher des actions pour compléter les faits à disposition. Les diagnostics élémentaires sont tous automatisés.

 Quand tout ne « match » pas,  il faut déterminer  si c’est un signal inconnu ou une variante d’un mode d’émission connu. Et faire l’analyse des causes.Et compléter en conséquence la base de données. Tant qu’on a pas « légiférer » sur le type de problème rencontré, c’est un opérateur expert qui décide. On dispose donc d’une pseudo-réalité terrain.

Pour traiter automatiquement ces situations d’échec on envisage l’utilisation :

- D’un apprentissage d’arbres de décisions pour retrouver automatiquement le bon diagnostic. A ce niveau l’explication (retour aux causes) est indispensable.

- De régles locales définies par l’expert sur les noeuds terminaux.


Pour l’apprentissage, nous envisageons d’utiliser :

- une technique rapide ne donnant pas forcément d’explication pour approcher la performance décisionelle que nous pourions atteindre

- Une technique à base d’arbres de décision pour avoir la possibilité d’expliquer le raisonement (et à terme de le compléter)

Nous avons réalisé il y a 20 ans un procédé type CART avec apprentissage local de densités de probabilités par Kernel. Dans le cadre d’une thèse nous aimerions approfondir la pertinence de ce type de technique avec les forets aléatoires. Il faudra aussi compléter (voir plus loin).

Dans le cadre de l’apprenti, nous voulons réaliser un véritable prototype travaillant sur données réelles (d’où une nécessité d’habilitabilité de celui-ci au niveau confidentiel requis). Et mettant en œuvre les techniques que nous trouvons sur étagère, puis les techniques plus raffinées extraites de la thèse.

Sur les nœuds terminaux de l’arbre, il pourrait être nécessaire d’améliorer le traitement en lançant des diagnostics partiels plus élaborés, répetoriés ou construis adhoc à la premiere fois ou le cas serait rencontré. Pour cela des régles simples de déclenchement d’action et de décision semblent idéales. Se posera alors le problème du maintien en cohérence des systèmes locaux de régles et les problèmes de généralisation et spécialisation.

Contact : Jean-Francois Grandin <jean-francois.grandin@fr.thalesgroup.com>

**THALES**

See {{ ::propositiondethese_tlasome_lip6.pdf |}}