PostDoc position in BCIs (Paris, France)

A one-year post-doctoral position in EEG-based Brain-Computer Interfaces (BCIs) is currently open at the INSEP Research Department in Paris. For this position, the candidate is expected to have a PhD in the field of BCIs or closely related fields. More specifically, she/he should have a solid training in BCIs, EEG signal processing, machine learning and fast calculations for real time applications. The candidate should also possess a strong programming background and statistical skills (MATLAB, C++). Strong language and writing skills in English are also required (note: speaking French is not required). The salary will be adjusted to the candidate's postdoctoral experience.

Supervisors:
Claire Calmels, PhD, HDR, Research Department, INSEP, Paris
Marc Elipot, PhD, Department of Innovation and Technological Development, INSEP, Paris

Location:
Institut National du Sport, de la Performance et de l'Expertise (INSEP), 11 avenue du Tremblay, 75 012 Paris, France

Instructions to apply:
Please send a complete CV, a 2-page cover letter, your most representative publications and contact information of two references by August 15th to This email address is being protected from spambots. You need JavaScript enabled to view it.

Desired starting date: November 1st, 2015

Feel free to contact us for more information.

Claire Calmels, PhD, HDR,
INSEP, Research Department,
11 avenue du Tremblay,
75 012 Paris
Tel: +33 (0)1 41 74 43 73 or +33 (0)6 37 30 16 31
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Postdoc position: Real-time 3D brain-activity visualization (EEG)

Postdoc position: Real-time 3D brain-activity visualization (EEG)

Location: Inria Rennes / France.

The position is within the Labex CominLabs project SABRE in collaboration between Inria and Telecom Bretagne. The project concerns developing real-time EEG source localization methods in software and hardware using either portable or high-density EEG devices (e.g. 256 electrodes) with applications in Brain-Computer Interfaces (BCI), neurofeedback, and re-education. The offered position centers around proposing and testing novel real-time visualization methods in this context.

Hiring date/start: End of 2015

For more information, please see

http://openvibe.inria.fr/openvibe/wp-content/uploads/2015/05/position-PostdocVisualizationSABRE.pdf

Keywords: EEG, BCI, scientific and medical visualization, inverse models, signal processin

Post-doc at Gipsa-lab/IMS

Post-doc subject proposal: Statistical learning in the space of SPD matrices: Applications to electro-encephalography and computer vision
Duration: 2 years
Tentative start date: October 2015
Supervisors: Christian Jutten and Marco Congedo (Gipsa-lab UMR 5216), Yannick Berthoumieu and Salem Said (IMS UMR 5218)
Context: This post-doc takes place in the context of the CHESS (Challenges in Extraction and Separation of Sources) research project, which was awarded with an ERC advanced grant in 2012. It is jointly supervised by scientists from Gipsa-lab and IMS laboratories, and will involve stays in both laboratories (Grenoble and Bordeaux, respectively).
Contact: This email address is being protected from spambots. You need JavaScript enabled to view it.This email address is being protected from spambots. You need JavaScript enabled to view it.

More information is available here.

Postdoc position: Real-time 3D brain-activity visualization (EEG) at INRIA Rennes (France)

The position is within the Labex CominLabs project SABRE in collaboration between Inria and Telecom Bretagne. The project concerns developing real-time EEG source localization methods in software and hardware using either portable or high-density EEG devices (e.g. 256 electrodes) with applications in Brain-Computer Interfaces (BCI), neurofeedback, and re-education. The offered position centers around proposing and testing novel real-time visualization methods in this context.

Hiring date/start: End of 2015

For more information, please see http://openvibe.inria.fr/openvibe/wp-content/uploads/2015/05/position-PostdocVisualizationSABRE.pdf

Keywords: EEG, BCI, scientific and medical visualization, inverse models, signal processing

PhD position with INRIA Montpellier, France

Stroke is caused when an artery carrying blood from heart to an area in the brain bursts or a clot obstructs the blood flow thereby preventing delivery of oxygen and nutrients. About half of the stroke survivors are left with some degree of disability where the impairment of motor control has been mentioned most frequently as the most important disability. Therefore, innovative methodologies for stroke neurorehabilitation are urgently required to reduce long-term disability.

Neuroplasticity is the ability of the central nervous system to respond to intrinsic or extrinsic stimuli by reorganizing its structure, function and connections. Neuroplasticity is involved in post-stroke restorative rehabilitation of upper-limb function, but also can cause maladaptive functional outcomes, which can compromise re-gain of function via implementation of sub-optimal compensatory movement strategies. Such neuroplastic changes can be facilitated with noninvasive brain stimulation (NIBS) techniques, such as transcranial direct current stimulation (tDCS). tDCS - an electrically based intervention directed at the central nervous system level - is a promising tool to facilitate neuroplasticity in stroke rehabilitation. In this work, we investigate on a physiological signal changes appearing on functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) neuroimaging systems to objectively quantify the progress of a chosen tDCS treatment regime, correlating outcome with brain activation patterns as a marker of the underlying neuronal plasticity. Here, it was postulated that tDCS (Dietzel and Heinemann 1986) that perturbs hemodynamic (fNIRS) and electrophysiological (EEG) responses where the interactions between the hemodynamic and electrophysiological responses, captured with NIRS-EEG joint modeling, may provide an assessment of neurovascular coupling. Such an approach is novel since it introduces neuroimaging in a field so far not accessible by existing technology. We use adaptive identification techniques to correspond to the time-variances as previously applied to other application for muscular response changes.

Applications are due by April 30, the position starts in October or later. Supervisor: This email address is being protected from spambots. You need JavaScript enabled to view it. (INRIA, Universite de Montpellier, France).

Title: Computational modeling for brain dynamics time-variance evoked by noninvasive brain stimulation. Keywords: Computational modeling, Neuroplasticity, Adaptive tracking, Brain dynamics, Signal processing