10 machine-learning PhD scholarships at Inria

PhD Position F/M Machine learning for efficient bimodal EEG-fMRI

interface (restorative BCI), consist in providing real-time feedback to a patient about his or her own brain activity in order to learn how self-regulate specific brain regions and help him or her perform a

PhD Position F/M [Campagne doctorants] on distributed automated machine

of Inria and will be supervised by Nikolaos Georgantas ([email protected] ) and Maroua Bahri ([email protected] ). Mission confiée Automated Machine Learning (AutoML) is an approach

PhD Position F/M Campagne/Welcome Package - Learning robotic manipulation

computer vision and robotics, the WILLOW team has consistently produced high-quality research, resulting in publications in major journals and conferences. As part of the team, you will have access to a well

PhD Position F/M -- Campagne Doctorant -- Explainable Deep Learning

, including expertise with frameworks such as PyTorch. - Advanced knowledge in Machine Learning and Pattern Recognition. - Expertise in BioMedical Image Analysis. - Strong foundation in applied mathematics and

PhD Position F/M Multimodal Speech Analysis for Early Detection of Crohn's

facial expressions and modifications in speech patterns using NLP and machine learning techniques. This will be achieved by analyzing video recordings of multiple patients, with each recording annotated by

PhD Position F/M Efficient Deep Learning (IDP 2024)

optimize the training and inference of modern deep learning architectures. Potential applications will include, but not be limited to, computer vision, natural language processing, climate, etc. References

PhD Position F/M Campagne doctorant 2024 - Emergence of mesoscale

cluster computer system to realize big-data analysis and simulations. Mission confiée Context of the project Artificial Intelligence (AI) and especially Deep Learning (DL) have undergone many successes in

PhD Position F/M Developing a deep learning framework to design cyclic

to inhibit the PPI formed between RBD and ACE2 is a very active field of research [5]. Moreover, the recent advances of machine learning and deep learning in the CASP competition and the outbreak of AlphaFold2

PhD Position F/M Trustworthy AI hardware architectures

, still energy efficient. Compétences Required technical skills: Good knowledge of computer architectures and embedded systems Machine Learning (pytorch/tensorflow) HW design: VHDL/Verilog basics, HW

PhD Position F/M Embedded AI: Graph Neural Networks in Lossy Embedded

. Supervised learning is one of the main branches in Artificial Intelligence (AI). Training a model requires an ensemble of data to train on. Each data item is associated with a label, which is the best