Search for a funded project
LOw-dimensional ferromagnetic units towards ValuablE Magneto-Electrics – LOVE-ME
We propose an original and thoughtful approach for designing magnetoelectric properties in inorganic compounds, dealing with low dimensional ferromagnetic units (0D blocks, 1D chains, 2D layers) and their alignment under field through metamagnetic transitions. Our candidates possess collinear or canted macrospins of high spin magnetic cations (M = Fe2+, Co2+, Mn2+), separated by non-magnetic and electrical insulating spacers or large cations building up the insulating properties.
LUminescent nanocoMposites by pulsed Injection of solutions iN plasmA – LuMINA
times identified in the Web of Science in March 2021 on "NC", "NC based on ZnO NPs", and "NC SiO2 and
Lab-in-Droplet platform for glycoprotein biomarker discovery: from device conception towards diagnostic applications – DropLab
This Lab-in-Droplet will unprecedentedly offer both efficient sample treatment and resolute analytes separation within sub µL droplets. This will be the first platform able to couple sample treatment and analyte separation modules without any problem of working volume mismatch, thus solving the instrumental and methodological bottlenecks currently encountered in analytical module integration.
Laboratory for Biomedical Image Management Applications – GinesisLab
Technological Research Team within the framework of the 2021-2025 contract of the institutional research organism
Laboratory of Alliances on Nanosciences - Energy for the Future
and 5 additional Equipments have been funded. In 2021, we have also organized a Call of Chaire of Excellence [...] projects have been funded. Through our PhD Call in 2021, 9 new PhD students have been recruited following [...] The publications acknowledging LANEF reaches 42 in 2021. We notice an impact on the exploitation of results
Laser Plasma Electron Acceleration with kHz Lasers – HighRep
Laser-plasma acceleration is an emerging and promising technique to produce electron beams in a compact way. In most cases, 100 TeraWatt or even PetaWatt laser systems, operating at Herz or lower, are used to accelerate electrons to GeV energies. However, many applications would benefit from higher rates, at kHz or even higher. This project proposes to develop laser-plasma acceleration at kHz.
Learning Intelligible Task Models for Cobots Programming – Prog4Yu
Learning of Intelligent Task Models for Cobot Programming
Learning Reasoning, Memory and Behavior – REMEMBER
We will focus on methodological contributions (models and algorithms) for training virtual and real agents to learn to solve complex tasks autonomously, targeting terrestrial mobile robots, typically service robots; industrial cobotics; autonomous vehicles; UAVs; humanoid robots. In particular, intelligent agents require high-level reasoning capabilities, situation awareness, and the capacity of robustly taking the right decisions at the right moments. The required behavior policies are complex, since they involve high-dimensional input spaces and state spaces, partially observed problems, as well as highly non-linear and entangled interdependencies. Learning them crucially depends on the algorithm’s capacity of learning compact, structured and semantically meaningful memory representations, which are able to capture short and long range regularities in the task and the environment. A second key requirement is the ability to learn these representations with a minimal amount of human interventions and annotations, as the manual design of complex representations is up to impossible. This requires the efficient usage of raw data through the discovery of regularities by different means: supervised, unsupervised or self-supervised learning, through reward or intrinsic motivation etc.
Learning causal effects between phenome and exposome from large amounts of heterogeneous data in human complex diseases – GePhEx
Learning causal effects between phenome and exposome from large amounts of heterogeneous data in human complex diseases.
Learning to synthesize 3D dynamic human motion – 3DMOVE
It has recently become possible to capture time-varying 3D point clouds at high spatial and temporal resolution, which allows in particular for high-quality acquisitions of human motion. Currently, first tools to process and analyze the data in a robust and automatic way are being developed. Such tools are critical to learning generative models of dynamic human motion. The objective of 3DMOVE is to compute high-quality generative models from a database of dense 3D motion sequences of humans.
