Sort by
Refine Your Search
-
The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning
-
in Artificial Intelligence (Machine Learning and Statistics) at CentraleSupélec, · Joël Eymery, Head of the Nanostructures and Synchrotron Radiation Team at CEA Grenoble, · Jean-Sébastien
-
technology is reducing the write current, which is intrinsically linked to the charge-to-spin current conversion ratio (), a key parameter defining the efficiency of SOT materials. The TopMemo project aims
-
with two new cryostats ranging from room temperature to millikelvin and can reach large magnetic fields. Our expertise lies in electric, thermoelectric, and thermal experiments for studying quantum
-
various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
-
to preserve the internal charge and handle the output signal of the RE (buffering function, polarity and gain adjustment). More precisely, a new embedded analog system will be developed, tested and evaluated
-
. Responsibilities will include: Developing expertise in audiological test batteries Data wrangling, cleaning, and feature engineering Applying and implementing statistical or machine learning methods, depending
-
of the project is to exploit such data to develop generative models for aptamer design. The candidate is expected to have a strong background in machine learning and statistical physics, with a real interest for
-
the electrical excitation of magnetization dynamics by torques, the different channels related to spin dynamics and orbital dynamics need to be disentangled, which we want to accomplish by experiments involving
-
various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly