Sort by
Refine Your Search
-
at developing new stacks of epitaxial layers containing Gallium Nitride (GaN) on Silicon substrate to demonstrate a power transistor capable of withstanding voltages higher than 1200 V. In particular, the project
-
transfer (MNT) reaction. The objective is to study the mechanism of the MNT reaction and its ability to produce heavy nuclei that are different and richer in neutrons compared to the fusion-evaporation
-
current health and safety regulations in laboratories, particularly in NMR 3) Interpersonal and soft skills - Strong ability to work independently - Proactive approach to research and scientific curiosity
-
condensed matter physics • Ability to learn and develop skills in analytical computation, theoretical modelling and numerical simulations, in particular the numerical solution of partial differential
-
development. The project will consist in the development of organometallic platforms based on a sustainable, non-toxic and abundant metal, manganese (Mn). Its ability to stabilize a large number of oxidation
-
Additional Information Eligibility criteria Ability to design and implement behavioral protocols Knowledge of statistics Experience in signal analysis Experience in agent-based modeling Proficiency in Python
-
for autonomous vehicles, and exoplanet detection. Among the various platforms capable of generating frequency combs, high-quality-factor resonators stand out for their ability to produce broad and stable combs
-
potentially integrated route to generate coherent THz radiation, while offering clear knobs—optical power per line, coherence, stability, and spectral bandwidth—to optimize the resulting THz performance
-
to renewable energy sources. Thermodynamic cycles (power generation cycles, refrigeration cycles, heat pumps) play a central role in this transformation, but their optimal design remains a complex scientific
-
of AI systems by a factor of 10,000 compared to conventional software solutions. In this context, the MARMOTTE project (Mott based nano-memristors networks for ultra-low-power neuromorphic computing) aims