Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
- Solid knowledge of existing literature in optimization and/or symbolic computation - Strong skills in programming with scientific and/or symbolic computing tools Website for additional job details https
-
possible sounding capabilities with current laser-produced sources, and (2) implementing experiments to test the predictions of these calculations and optimize the sources. The missions follow these lines
-
Department (DRIS), you will participate in research activities on the optimization of non-Newtonian fluid injection for the decontamination of polluted soils. Tests will be conducted, in 1D columns, in 2D
-
under periodic conditions. SOC and excited-state geometry optimizations will help identify ISC/RISC probabilities and the specific components involved. These insights will clarify how each molecular
-
experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
-
and mRNA translation. The successful candidate will establish live imaging tools to analyse translation dynamics in regenerating axons, using an ex vivo culture model previously optimized (Schaeffer et
-
. This is only possible thanks to the involvement of the Univ-Lille partner, which is developing these highly optimized data structures and partners (Paris-Saclay Univ) with a solid expertise in exploiting
-
(cholesterol esters) and proteins; in particular, the person recruited will be responsible for optimizing the parameters for neutral lipids. • Develop and implement new methodologies for analyzing molecular
-
” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a
-
optimizations are still needed to adapt the translation of these mRNAs to the cell types of interest. As part of a collaboration with Chantal Pichon's team (University of Orleans), this project aims to use