Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
an asset. The position requires a high level of experimental skills to operate sophisticated instruments, as well as strong analytical abilities to interpret measured data and design innovative experiments
-
/or experience in microfluidics and image processing. Strong interpersonal skills, teamwork, scientific curiosity, and ability to synthesize information. Where to apply Website https://emploi.cnrs.fr
-
be developed in close interaction. Observations made on real leaves will guide the design of the biomimetic systems, while microfluidic experiments will make it possible to isolate and control
-
. Preferred: background and/or experience in microfluidics and image processing. Strong interpersonal skills, teamwork, scientific curiosity, and ability to synthesize information. Where to apply Website https
-
–2 at LMA, Marseille– Device design and construction, supervised by Renaud Côte with support from Vincent Roggerone and Sandrine Rakotonarivo. Year 3 at CRNL, Lyon– Live-animal experiments supervised
-
(Label of Excellence - 00180410, Normandy Region) which aims to develop a new perspective on interfacial interactions for a tailored design of porous materials. This project aims to apply and combine
-
. • Very good knowledge of Python • Experience with machine learning libraries such as PyTorch, JAX, TensorFlow or equivalent • Knowledge of micromagnetic simulations • Interest in inverse-design methods
-
design workflows for nanoporous carbon electrodes for sodium-ion batteries. The objective is to accelerate the exploration of virtual carbons with varied microstructures by combining numerical structure
-
perfusion and mechanical stimulation in tumor tissues to investigate their poromechanical properties and optimize molecular transport within explants. The successful candidate will be involved in: - Designing
-
of behavioral traces or behavioral metrics in VR. Mastery of experimental methodology (between-subjects design, multiple dependent variables, control of biases). Experience in designing and conducting studies