Call for applications | PhD & Postdoctoral positions

• Machine Learning for Computer Simulation, Motonubu Kanagawa
• AI models hybridizing machine learning and argumentation to counter online misinformation and cyberbullying, Charles Bouveyron
• Deep Generative Models for the Joint Analysis of Networks and Continuous data, Charles Bouveyron
• Incentives for Federated Learning, Giovanni Neglia
• Identification of molecular patterns to inform about chemical safety, Vincent Vandewalle
• Argument Quality Assessment and Improvement, Serena Villata
• Hybrid Argument Mining and Reasoning, Serena Villata
• Argument-based counter narratives generation to fight online hate speech, Elena Cabrio
• Accounting for uncertainty in machine learning: generative, Bayesian, conformal?, Pierre-Alexandre Mattei
• Geometry, stratification and applications of structured correlation matrices, Xavier Pennec
• AI for archaeozoology:  learning methods to identify and cluster faunal remains, Marco Corneli
• Predicting smell by physiologically inspired deep learning modelsI, Marco Gori

• Novel tensor decompositions for atrial fibrillation analysis, Vicente Zarzoso
• Semantic Modelling within Transformers for Action Detection in Untrimmed Videos, François Bremond
• Joint Learning from Medical Images & Text Reports – application to Ultrasound Imaging, Nicholas Ayache
• Machine and Deep Learning models for predicting response to immunotherapy in oncology from a federated multicenter database, Olivier Humbert

• Attention mechanisms for graphical models, with applications to protein structure analysis, Frederic Cazals
• Identification of molecular patterns to inform about chemical safety, Vincent Vandewalle
• Spatial imaging of the human lung from health to pathologies, Pascal Barbry
• Super-resolution in fluorescence microscopy images by generative learning methods, Laure Blanc-Féraud
• Reconstruction of filaments in fluorescence microscopy by off-the-grid methods, Laure Blanc-Féraud
• Predicting smell by physiologically inspired deep learning modelsI, Marco Gori

• Artificial intelligence for sustainable technological development, Marina Teller
• AI models hybridizing machine learning and argumentation to counter online misinformation and cyberbullying, Charles Bouveyron
• Incentives for Federated Learning, Giovanni Neglia
• Attacks and Defenses against Federated Learning, Melek Önen

You are a candidate: here is how to apply

The applicant must send the following documents directly to the Chairholder:

• Letter of recommendation of the supervisor indicated above.
• Curriculum vitæ.
• Motivation Letter.
• Academic transcripts of a master’s degree(s) or equivalent.
• At least, one letter of recommendation.

Please note: start of the thesis before the end of December 2023

You are a 3IA Chairholder: here is your calendar

• Submission of a PhD thesis proposal by the 3IA Chairholder: deadline 28 April 2023
• Submission of the selected candidate's application by the Chairholder: deadline 26 May 2023
  • File to be uploaded on EasyChair
  • All the requested documents must be gathered and concatenated in a single PDF file named in the following format: LAST NAME of the candidate_Last Name of the supervisor_2023.pdf
• Evaluation from the Scientific Committee of the Institute: June 21st, 2023