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.
First-year Internship
Period: from the beginning of April to the end of August (at least 4 months)
Defence: 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)
Defence: 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.
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.
For M1 students: Access internship proposals from the Polytechnique engineering student page. — 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:
CALYPSO project, Lille University (M2) Master internship in AI and Computer vision applied to neurosciences and phycological disorders: link to the proposal
Thales & LIP6 Sorbonne Université (M2, possibility to pursue with a PhD.) Master internship in Data Visualization applied to Trustworthy AI of critical systems: link to the proposal
LIP6 Sorbonne Université & CEA (M2, possibility to pursue with a PhD.) Master internship in Data Visualization: link to the proposal
Ideactiv (M2, french speaker preferred, possibility to pursue with a PhD.) Master internships in Natural Language Processing applied to Culture. See the announcement here: link to the proposals
LASTIG lab (M2) https://www.umr-lastig.fr/ (M2) Master internship in the visualization of Urban multi-modal data from the GEOVIS team (Visualization, Interaction and Immersion) - Visual computing topic (no AI): link to the proposal
GE Healthcare France (M1 or M2) link to the proposals
Dassault systems (M2 only) link to the proposals
Adobe - internships in computational photography in San Jose, USA ——– 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.
DeepMind - Call for Student Researchers at Google DeepMind ——– 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!
Artefact - Deep learning, Computer Vision - 19 rue Richer, 75009, Paris, www.artefact.com * Topics
Laboratoire I3S (CNRS UniCA) Equipe Mediacoding - Sophia Antipolis 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
Seelab - Hybrid (remote + on-site in Paris or Nantes)
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
This list is kept here as inspirations/ideas on companies your could contact to find an internship.
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”
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
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
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
ARTEFACT Paris - Research Internship in Computer Vision “Scalable Multi Objects Tracking for Retail”
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
GLEAMER - 117 Quai de Valmy - 75010 Paris - AI engineer trainee
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
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
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
Duration : The 6-month internship Périod : betwen middle of -january and middle of July 2023 (WARNING: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
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”
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
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
INRIA – Grenoble (Fr) - M2 internship: Video-based dynamic garment representation and synthesis
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
PRIMAA – Paris (Fr)
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
Worldline – Human / bot behavior identification – Lyon (Fr)
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
Inria – Rationalization of CAD assemblies – Sophia-Antipolis (Fr-near Nice) ; Master-level internship, could be extended to a PhD
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/
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)
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
Inria – Subcell erosion for terrain generation – Sophia-Antipolis (Fr-near Nice)
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/
Inria – Instant generation of geomorphologically accurate terrain – Sophia-Antipolis (Fr-near Nice)
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/
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