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--- internships [2024/12/12 13:02] – [Internship proposals 2024-2025] respai-vic
+++ internships [2025/09/10 16:42] (current) – [Internship proposals 2025-2026] respai-vic
@@ Line 1: / Line 1: @@
 ==== General Requirements ====
-For first and second year, internship topics are to be validated by the academic co-directors of the MScT (Marie-Paule Cani, Johannes Lutzeyer, Erwan Le Pennec and Aymeric Dieuleveut) by sending an email mentioning the subject of the internship, the duration, the supervisor and the location of the internship. Once the internship topic is validated, please put Aymeric (for M1 students) or Johannes (for M2 students) as the "Enseignant référent" at Ecole Polytechnique.
+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**
@@ Line 7: / Line 7: @@
 Period: from the beginning of April to the end of August (at least 4 months)
-Defence: First half of September
+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.
@@ Line 16: / Line 16: @@
 Period: from the beginning of April to the end of September (at least 5 months)
-Defence: First half of September (the internship can be continued after the defence)
+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.
@@ Line 32: / Line 32: @@
   * References - please cite the journal/conference where the papers were published, if applicable, not the Axiv ref.
-The oral examinations 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.
+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.
-=============== Internship proposals 2024-2025 ===============================================
+** 💡💡 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>**
---- Forwarded from Damien Rohmer: ----
 If you would like to see more internship proposals in Visual Computing, preselected for their decent research components, please follow this procedure:
@@ Line 47: / Line 61: @@
     * login: your email address
     * password: 3AstudentDIX
+=============== Internship proposals 2025-2026 ===============================================
+**<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]]
+=============== Internship proposals 2024-2025 ===============================================
 **<color #e32d2d> CALYPSO project, Lille University (M2) </color>**
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 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, CNRS (M2, possibility to pursue with a PhD.) </color>**
+**<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]]
@@ Line 137: / Line 168: @@
   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