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--- internships [2025/11/13 12:53] – [Internship proposals 2025-2026] respai-vic
+++ internships [2025/12/08 13:29] (current) – [Internship proposals 2025-2026] respai-vic
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 =============== Internship proposals 2025-2026 ===============================================
+**<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>**
@@ Line 129: / Line 218: @@
   * 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 ===============================================