Phd subjects of Doctoral School SPI 2024 proposed and applications procedures
Receipt of applications before midnight the 14th of May 2024;
Hearings: the first week of June 2024.
The application file contains the candidate's results (M1+ S3 M2) and rankings (M1 if M2 is not finished), as well as the assessment of his or her master's supervisor and master's supervisor.
Each candidate is auditioned for 10 min, followed by 10 min of questions. Each candidate presents his or her background and the thesis subject on which he or she is applying.
ICCF
Institut Pascal
- Subject 1: Impact of bio-based materials on the intensity of urban heat islands;
- Subject 2: Characterisation of the couplings between the phase transformation and the thermomechanical behaviour of shape memory alloys;
- Subject 3: Development of flax/thermoplastic composites - characterization of their properties and durability;
- Subject 4: Experimental and numerical study of air flow and pollutant dispersion in a ventilated and differentially heated room;
- Subject 5: Semi-supervised learning for 3D reconstruction of environments from images;
- Subject 6: Unsupervised 2D and 3D multi-modal and temporal registration of vascular networks via hybrid methods combining variational and physical principles, graph-based approaches and deep-learning models;
- Subject 7: Studies of the potentialities of nano-functionnalized matrix as sensing layer of microsensors dedicated to hydrogen leakage monitoring (H2);
- Subject 8: Influence of natural and imparted ageing on the toughness of wood;
- Subject 9: Experimental and numerical study of the mechanical behavior of demountable and composite floors made of steel, timber, and concrete;
- Subject 10: Multimodal contact servoing on a deformable liver;
- Subject 11: Design of a variable stiffness overtube for robotic colonoscopy;
- Subject 12: Devices based on micro- and nanostructures grown by Vapor Phase Epitaxy (VPE) processes;
- Subject 13: Building a local supply of raw materials for the French textile industry;
- Subject 14: Machine learning approaches for uncertainty quantification due to numerical simulation process of Electromagnetic Compatibility problems.
Limos
- Subject 1: On exact powers of graphs;
- Subject 2: Improvement of the LoRaWAN throughput based on physical characteristics of LoRa frames;
- Subject 3: Combinatorics behind routing and spectrum assignment in modern optical telecom networks;
- Subject 4: Luminous Robot Swarms in Adversarial Discrete;
- Subject 5: Efficient enumeration of potential maximal cliques in a graph.
Laboratoire de physique corpusculaire
- Coming soon.