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

PhD Position: Brain-Computer Interfaces in Cognitive Rehabilitation after Stroke

BrainStateDecoding Lab of Dr. Michael Tangermann (Computer Science Dept.); payment level: TV-L E13 (65%); duration: 3/2015-2/2017

Brain-Computer Interface (BCI) systems make use of machine learning methods to cope with the challenges which appear during the decoding of individual brain signals in real-time. Within the BrainLinks-BrainTools cluster of excellence at the University of Freiburg (Germany), we evaluate whether BCI methods can be applied clinically outside of classical control paradigms.

The PhD student will explore the use of BCI methods to support neurological rehabilitation training of speech and attention-related deficits after stroke.
Scientific challenges comprise the development and investigation of brain signal analysis methods capable to describe rapid fluctuations of brain states and to assess the dynamics of network structures connecting brain areas.

Working Areas (among others):

  • Theories (statistics, mathematics) and algorithms in the field of machine learning, with special emphasis on adaptive methods for the real-time decoding of mental states; software implementations thereof.
  • Conducting EEG studies with healthy controls and stroke patients.
  • Analysis of EEG experiments.
  • Supervision of Bachelor students.
  • Scientific dissemination of results (conferences, publications).

Requirements:

  • Excellent Master studies on Computer Science, Mathematics, Electrical Engineering, Biomedical Engineering, Cognitive Science or closely related fields.
  • Knowledge in theory and methods of machine learning / artificial intelligence; very good math knowledge (specifically in probability theory, statistics, linear algebra).
  • Good knowledge about the design, the analysis and implementation of algorithms; experience with mathematical software (e.g. Matlab).
  • Hands-on experience in the design, execution and analysis of electrophysiological experiments, and in signal processing of EEG-, EMG-, EOG- or ECoG data.
  • Excellent communication skills in English

The BrainStateDecoding Lab:
The international lab is embedded into the Cluster of Excellence BrainLinks-BrainTools at the University of Freiburg. The cluster provides supporting career actions for PhD students. Tight collaborations with other BLBT groups are the basis for investigating novel machine learning approaches for the real-time analysis of brain signals. The activities range from theory development to BCI applications in a clinical context and for healthy users. Implementing an equal-chances policy and family-friendly working conditions, we explicitly encourage applications of female researchers. Handicapped applicants will be given priority to non-handicapped applicants, if they have comparable qualifications. Further information: www.bsdlab.uni-freiburg.de, www.brainlinks-braintools.uni-freiburg.de and via Dr. Tangermann.

How to apply:
Please state the position code BCI-4 when sending your application documents (including a CV, statement of your research interests, list of publications, references, Master and Bachelor degrees and course lists) as a single PDF document via email to Dr. Michael Tangermann (This email address is being protected from spambots. You need JavaScript enabled to view it.).