Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
or machine learning applied to brain signals would be an advantage. We are seeking a highly motivated, rigorous and inquisitive researcher, ready to commit to a project at the interface between basic and
-
inspiring novel strategies for brain-machine interfaces. Indeed, some studies have found HD signals to be anticipatory, depending on the degree to which movements are active, volitional or predictable. After
-
prostheses, and more broadly the emergence of brain–machine interfaces capable of bidirectional communication with the nervous system. In addition, they open new perspectives for personalized medicine
-
to the development of software platforms for brain data analysis, with potential applications in healthcare technologies. It is important that the candidate must have strong programming skills and experience in
-
faible résistance doit réussir à se former, par la localisation de la déformation sur une (mince) interface de découplage entre deux plaques lithosphériques, plaques dont le 'coeur' peut-être très
-
the impact of collective effects in high space-charge regimes. The Accelerators and Ion Sources Pole of LPSC is involved in the design, construction, and operation of the PERLE machine, particularly in
-
Graphics, 1(4), 350-360. Available at: https://doi.org/10.1109/2945.485622 [7] Meltzoff, A.N. (1995). Understanding the intentions of others: Re-enactment of intended acts by 18-month-old children
-
research centre dedicated to understanding normal and pathological brain function and developing new diagnostic and therapeutic approaches. Website: https://neurosciences.univ-grenoble-alpes.fr You will be
-
https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/137045 Requirements Specific Requirements Nous recherchons un(e) candidat(e) motivé(e) ayant une formation en probabilités, en physique statistique
-
Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | about 2 months ago
collaboration with L. Bonati at IIT Genova, who developed the library mlcolvar, https://github.com/luigibonati/mlcolvar ). 2) Compare the data-science dimensional reduction approaches above, with machine learning