Dear colleagues,
We are inviting participation to biometric competition on "6th *Sclera
Segmentation
Recognition Benchmarking Competition(SSBC 2019)", *in conjunction with the
12th* IAPR **International Conference on Biometrics (ICB 2019)*.
Details about the competition can be found at
https://sites.google.com/view/ssbc2019/home
Please find a call for participation flyer attached with the email. Please
feel free to register for the same.
*We will** welcome the top ranking participant to join as co-author of the
technical report of the competition that will be submitted to ICB 2019**.*
Feel free to contact Abhijit Das if you have any further questions.
Kindly circulate this email to others who might be interested.
We look forward to your contributions!
Best regards
Organizers SSBC 2019
Abhijit Das (Inria, France)
Umpada Pal (ISI, Kolkata, India)
Michael Blumenstein (UTS , Australia)
Dear colleagues,
We are inviting paper submissions for a special session on “Human Health
Monitoring Based on Computer Vision”, as part of the 14th IEEE
International Conference on Automatic Face and Gesture Recognition (FG’19,
http://fg2019.org/), Lille, France, May 14-18, 2019. Details on the special
session can be found in the attached call for paper and at
http://fg2019.org/participate/special-sessions/hhmbcv/.
IMPORTANT DATES:
Full Paper Submission: Dec 14th, 2018
Acceptance Notification: Jan 21st, 2019
Camera-Ready Paper Due: Feb 15th 2019
Feel free to contact Abhijit Das if you have any further questions.
Kindly circulate this email to others who might be interested.
We look forward to your contributions!
François Brémond (INRIA, France)
Antitza Dantcheva (INRIA, France)
Abhijit Das (INRIA, France)
Xilin Chen (CAS, China)
Hu Han (CAS, China)
2nd CALL FOR PARTICIPATION
The One-Minute Gradual-Empathy Prediction (OMG-Empathy) Competition
held in partnership with the IEEE International Conference on Automatic
Face and Gesture Recognition 2019 in Lille, France.
https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/omg_empathy.html
I. Aim and Scope
The ability to perceive, understand and respond to social interactions in a
human-like manner is one of the most desired capabilities in artificial
agents, particularly social robots. These skills are highly complex and
require a focus on several different aspects of research, including
affective understanding. An agent which is able to recognize, understand
and, most importantly, adapt to different human affective behaviors can
increase its own social capabilities by being able to interact and
communicate in a natural way.
Emotional expression perception and categorization are extremely popular in
the affective computing community. However, the inclusion of emotions in
the decision-making process of an agent is not considered in most of the
research in this field. To treat emotion expressions as the final goal,
although necessary, reduces the usability of such solutions in more complex
scenarios. To create a general affective model to be used as a modulator
for learning different cognitive tasks, such as modeling intrinsic
motivation, creativity, dialog processing, grounded learning, and
human-level communication, only emotion perception cannot be the pivotal
focus. The integration of perception with intrinsic concepts of emotional
understanding, such as a dynamic and evolving mood and affective memory, is
required to model the necessary complexity of an interaction and realize
adaptability in an agent's social behavior.
Such models are most necessary for the development of real-world social
systems, which would communicate and interact with humans in a natural way
on a day-to-day basis. This could become the next goal for research on
Human-Robot Interaction (HRI) and could be an essential part of the next
generation of social robots.
For this challenge, we designed, collected and annotated a novel corpus
based on human-human interaction. This novel corpus builds on top of the
experience we gathered while organizing the OMG-Emotion Recognition
Challenge, making use of state-of-the-art frameworks for data collection
and annotation.
The One-Minute Gradual Empathy datasets (OMG-Empathy) contain multi-modal
recordings of different individuals discussing predefined topics. One of
them, the actor, shares a story about themselves while the other, the
listener, reacts to it emotionally. We annotated each interaction based on
the listener's own assessment of how they felt while the interaction was
taking place.
We encourage the participants to propose state-of-the-art solutions not
only based on deep, recurrent and self-organizing neural networks but also
traditional methods for feature representation and data processing. We also
enforce that the use of contextual information, as well as personalized
solutions for empathy assessment, will be extremely important for the
development of competitive solutions.
II. Competition Tracks
We let available for the challenge a pre-defined set of training,
validation and testing samples. We separate our samples based on each
story: 4 stories for training, 1 for validation and 3 for testing. Each
story sample is composed of 10 videos with interactions, one for each
listener. Although using the same training, validation and testing data
split, we propose two tracks which will measure different aspects of
self-assessed empathy:
The Personalized Empathy track, where each team must predict the empathy of
a specific person. We will evaluate the ability of proposed models to learn
the empathic behavior of each of the subjects over a newly perceived story.
We encourage the teams to develop models which take into consideration the
individual behavior of each subject in the training data.
The Generalized Empathy track, where the teams must predict the general
behavior of all the participants over each story. We will measure the
performance of the proposed models to learn a general empathic measure for
each of the stories individually. We encourage the proposed models to take
into consideration the aggregated behavior of all the participants for each
story and to generalize this behavior in a newly perceived story.
The training and validation samples will be given to the participants at
the beginning of the challenge together with all the associated labels. The
test set will be given to the participants without the associated labels.
The team`s predictions on the test set will be used to calculate the final
metrics of the challenge.
III. How to Participate
To participate in the challenge, please send us an email to barros @
informatik.uni-hamburg.de with the title "OMG-Empathy Team Registration".
This e-mail must contain the following information:
Team Name
Team Members
Affiliation
Participating tracks
We split the corpus into three subsets: training, validation, and testing.
The participants will receive the training and validation sets, together
with the associated annotations once they subscribe to the challenge. The
subscription will be done via e-mail. Each participating team must consist
of 1 to 5 participants and must agree to use the data only for scientific
purposes. Each team can choose to take part in one or both the tracks.
After the training period is over, the testing set will be released without
the associated annotations.
Each team must submit, via e-mail, their final predictions as a .csv file
for each video on the test set. Together with the final submission, each
team must send a short 2-4 pages paper describing their solution published
on Arxiv and the link for a GitHub page to their solution. If a team fails
to submit any of these items, their submission will be invalidated. Each
team can submit 3 complete submissions for each track.
IV. Important Dates
25th of September 2018 - Opening of the Challenge - Team registrations begin
1st of October 2018 - Training/validation data and annotation available
3rd of December 2018 - Test data release
5th of December 2018 - Final submission (Results and code)
7th of December 2018 - Final submission (Paper)
10th of December 2018 - Announcement of the winners
V. Organization
Pablo Barros, University of Hamburg, Germany
Nikhil Churamani, University of Cambridge, United Kingdom
Angelica Lim, Simon Fraser University, Canada
Stefan Wermter, Hamburg University, Germany
--
Dr. Pablo Barros
Postdoctoral Research Associate - Crossmodal Learning Project (CML)
Knowledge Technology
Department of Informatics
University of Hamburg
Vogt-Koelln-Str. 30
22527 Hamburg, Germany
Phone: +49 40 42883 2535
Fax: +49 40 42883 2515
barros at informatik.uni-hamburg.dehttp://www.pablobarros.nethttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.htmlhttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/
Nanyang Technological University (NTU) in Singapore has open calls for several postdoctoral fellowships, which are also open for research on vision and perception. There are currently three labs in the area of vision research:
- Charles OR (charlesor(a)ntu.edu.sg<mailto:charlesor@ntu.edu.sg>)
Face perception, motion perception, form perception, EEG, eye movements, computational modelling, psychophysics;
http://research.ntu.edu.sg/expertise/academicprofile/Pages/StaffProfile.asp…
- Gerrit MAUS (maus(a)ntu.edu.sg<mailto:maus@ntu.edu.sg>)
Eye movements, eye blinks, filling-in, interpolation and extrapolation in vision, prediction, motion perception; psychophysics, fMRI, TMS;
http://blogs.ntu.edu.sg/perception
- Hong XU (xuhong(a)ntu.edu.sg<mailto:xuhong@ntu.edu.sg>)
Heading/Self-motion perception in navigation, face and object perception, attention and eye movements, virtual reality, EEG, electrophysiology, modelling, psychophysics;
http://www.ntu.edu.sg/home/xuhong/
We have access to state-of-the-art facilities for psychophysics, virtual reality, eye tracking, EEG, MEG, fMRI, fNIRS, TMS, and tDCS.
Feel free to contact any of us for more information or to discuss potential proposals.
The fellowship ad below (Deadline: 30 November) is currently offered by the College of Humanities, Arts, and Social Sciences, NTU.
There are two more opportunities available at NTU:
- for research related to Artificial Intelligence (Walllenberg - NTU Presidential Postdoctoral Fellowship, http://www.ntu.edu.sg/ppf/Pages/home.aspx),
- for research in any area by PhD graduates from Swedish Universities (Wallenberg - NTU Postdoctoral Fellowship, call open from Dec 1st, https://kaw.wallenberg.org/utlysningar/wallenberg-foundation-postdoctoral-f…)
Best Regards,
Charles OR, Gerrit MAUS, Hong XU
Assistant Professors (Psychology)
School of Social Sciences
College of Humanities, Arts, and Social Sciences
Nanyang Technological University, Singapore
======
The College of Humanities, Arts, and Social Sciences, Nanyang Technological University (NTU) invites applications from eligible candidates to join us as Postdoctoral Fellows for the Academic Year 2019.
The Postdoctoral Fellowships are for one year, renewable for a second year, subject to satisfactory performance. Applicants are strongly advised to explore the research interests of the College’s faculty members to identify potential faculty mentors.
Applicants must possess a doctoral degree issued no more than 3 years prior to the time of application (i.e. the degree must have been obtained after Jan 1, 2016). Candidates who are finishing up their degrees must have their doctoral degrees conferred by July 2019.
Owing to the interdisciplinary nature of the fellowship, applicants are expected to propose a research project to demonstrate how their expertise crosses different disciplines and relates to the specific Research Theme they are applying for.
Details are available at:
http://class.cohass.ntu.edu.sg/Research/Pages/Postdoctoral-Fellowship-2019.…
Applications and Reference Letters must reach the College by 30 November, 2018 (11:59pm Singapore Time UTC+8). Successful candidates are expected to commence their Fellowships in July or August 2019.
Owing to the tight deadline, interested candidates are invited to contact potential faculty mentors as soon as possible, with curriculum vitae and a brief research statement provided.
Application and enquiries should be addressed to:
The Associate Dean (Research)
College of Humanities, Arts, and Social Sciences
Email: AD-HASS-RESEARCH(a)ntu.edu.sg<mailto:AD-HASS-RESEARCH@ntu.edu.sg>
NTU is a young and research-intensive university ranking consistently amongst the top 10 in Asia and the 1st amongst young universities under 50. It has been ranked consistently and progressively under the top 100 universities in the world by the Times Higher Education since 2013, with its latest ranking at 51. Singapore is a fascinating, dynamic multi-cultural city in Southeast Asia with a large expat community, and a great hub for exploring neighbouring travel destinations.
=======
________________________________
CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents.
Towards a sustainable earth: Print only when necessary. Thank you.
Hi!
I am looking for a database of 3D models of famous faces.
I found Eric Baird's database at
http://www.relativitybook.com/CoolStuff/facebank.html, but was hoping
for additional celebrities.
If anyone has a database and is willing to share, or could point me to
a database, it would be very much appreciated.
Thanks!
Caspar
Apologies for cross-posting
***********************************************************************************
CBAR 2019: CALL FOR PAPERS
6th International Workshop on CONTEXT BASED AFFECT RECOGNITION
https://cbar2019.blogspot.com/
Submission Deadline: December 14th, 2018
***********************************************************************************
The 6th International Workshop on Context Based Affect Recognition (CBAR
2019) will be held in conjunction with FG 2019 in May 2019 in Lille
France – http://fg2019.org/
For details concerning the workshop program, paper submission, and
guidelines please visit our workshop website at:
https://cbar2019.blogspot.com/
Best regards,
Zakia Hammal
Zakia Hammal, PhD
The Robotics Institute, Carnegie Mellon University
http://www.ri.cmu.edu/http://ri.cmu.edu/personal-pages/ZakiaHammal/
CALL FOR PAPERS
IEEE Transactions on Affective Computing
Special Issue on Automated Perception of Human Affect from Longitudinal
Behavioral Data
Website:
https://www2.informatik.uni-hamburg.de/wtm/omgchallenges/tacSpecialIssue201…
I. Aim and Scope
Research trends within artificial intelligence and cognitive sciences are
still heavily based on computational models that attempt to imitate human
perception in various behavior categorization tasks. However, most of the
research in the field focuses on instantaneous categorization and
interpretation of human affect, such as the inference of six basic emotions
from face images, and/or affective dimensions (valence-arousal), stress and
engagement from multi-modal (e.g., video, audio, and autonomic physiology)
data. This diverges from the developmental aspect of emotional behavior
perception and learning, where human behavior and expressions of affect
evolve and change over time. Moreover, these changes are present not only
in the temporal domain but also within different populations and more
importantly, within each individual. This calls for a new perspective when
designing computational models for analysis and interpretation of human
affective behaviors: the computational models that can timely and
efficiently adapt to different contexts and individuals over time, and also
incorporate existing neurophysiological and psychological findings (prior
knowledge). Thus, the long-term goal is to create life-long personalized
learning and inference systems for analysis and perception of human
affective behaviors. Such systems would benefit from long-term contextual
information (including demographic and social aspects) as well as
individual characteristics. This, in turn, would allow building intelligent
agents (such as mobile and robot technologies) capable of adapting their
behavior in a continuous and on-line manner to the target contexts and
individuals.
This special issue aims at contributions from computational neuroscience
and psychology, artificial intelligence, machine learning, and affective
computing, challenging and expanding current research on interpretation and
estimation of human affective behavior from longitudinal behavioral data,
i.e., single or multiple modalities captured over extended periods of time
allowing efficient profiling of target behaviors and their inference in
terms of affect and other socio-cognitive dimensions. We invite
contributions focusing on both the theoretical and modeling perspective, as
well as applications ranging from human-human, human-computer and
human-robot interactions.
II. Potential Topics
Given computational models, the capability to perceive and understand
emotion behavior is an important and popular research topic. That is why
recent special issues on the IEEE Journal on Transactions on Affective
Computing covered topics from emotion behavior analysis “in-the-wild” to
personality analysis. However, most of the research published by these
specific calls treat emotion behavior as an instantaneous event, relating
mostly to emotion recognition, and thus neglect the development of complex
emotion behavior models. Our special issue will foster the development of
the field by focusing excellent research on emotion models for long-term
behavior analysis.
The topics of interest for this special issue include, but are not limited
to:
- New theories and findings on continuous emotion recognition
- Multi- and Cross-modal emotion perception and interpretation
- Lifelong affect analysis, perception, and interpretation
- Novel neural network models for affective processing
- New neuroscientific and psychological findings on continuous emotion
representation
- Embodied artificial agents for empathy and emotion appraisal
- Machine learning for affect-driven interventions
- Socially intelligent human-robot interaction
- Personalized systems for human affect recognition
III. Submission
Prospective authors are invited to submit their manuscripts electronically,
adhering to the IEEE Transactions on Affective Computing guidelines (
https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369). Please
submit your papers through the online system (
https://mc.manuscriptcentral.com/taffc-cs) and be sure to select the
special issue: Special Issue/Section on Automated Perception of Human
Affect from Longitudinal Behavioral Data.
IV. IMPORTANT DATES:
Submissions Deadline: 15th of January 2019
Deadline for reviews and response to authors: 06th of April 2019
Camera-ready deadline: 05th of August 2019
V. Guest Editors
Pablo Barros, University of Hamburg, Germany
Stefan Wermter, University of Hamburg, Germany
Ognjen (Oggi) Rudovic, Massachusetts Institute of Technology, United States
of America
Hatice Gunes, University of Cambridge, United Kingdom
--------------------------
--
Dr. Pablo Barros
Postdoctoral Research Associate - Crossmodal Learning Project (CML)
Knowledge Technology
Department of Informatics
University of Hamburg
Vogt-Koelln-Str. 30
22527 Hamburg, Germany
Phone: +49 40 42883 2535
Fax: +49 40 42883 2515
barros at informatik.uni-hamburg.dehttp://www.pablobarros.nethttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.htmlhttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/
Dear colleagues,
The Society for Affective Science is pleased to announce a Call for Abstracts for the SAS 2019 Conference at the Westin Boston Waterfront Hotel in Boston, MA, on March 21-23, 2019.
Abstract Submission Formats
In addition to invited sessions, we invite attendees to submit abstracts for posters and flash talk sessions. We welcome abstract submissions that describe new research within the domain of affective science. In line with our goal to facilitate interdisciplinary advances, we welcome submissions from affective scientists in any discipline (e.g., anthropology, business, computer science, cultural studies, economics, education, geography, history, integrative medicine, law, linguistics, literature, neuroscience, philosophy, political science, psychiatry, psychology, public health, sociology, theatre), working on a broad range of topics using a variety of measures. Authors at all career stages – trainees, junior faculty, and senior faculty – are encouraged to submit an abstract according to two presentation formats on any topic within the domain of affective science as follows:
1. A poster
2. A flash talk
Deadline for Receipt of Abstracts
Abstracts must be submitted by Friday, November 9, 2018, at 11:59 p.m. Baker Island Time (BIT; UTC-12) to be considered for inclusion in the program. Please review the abstract submission instructions carefully. Click here<https://t.e2ma.net/click/4fw8pd/824poyb/sqgu0q> to submit your abstract. All presenters must register and pay to attend the meeting. Notification of acceptance or rejection of abstracts will be emailed to the corresponding author by Friday, January 11, 2019.
Selection Process
All abstracts will be evaluated for scholarly merit by an interdisciplinary group of SAS Program Committee members using blind peer review. Abstracts are also selected at this time for Poster Spotlight presentations and consideration for poster and flash talk awards. Posters and flash talk award nominees will be evaluated during the conference by SAS faculty members. Reviewers do not review abstracts, posters, or flash talks on which they have a known conflict of interest. Awards will be announced at the conference during the closing ceremony.
Program Highlights
This year's invited program includes new and exciting interdisciplinary conversations in affective science. An opening session "Trajectories, Transitions, and Turning Points," features Phoebe Ellsworth, Valeria Gazzola, and Bob Levenson describing experiences, events, and findings that were key transitions points in their research programs and careers. The presidential symposium will be devoted to research on culture, ethnicity, and emotion. This year's program will also feature a symposium on emotion and health jointly sponsored by SAS and the American Psychosomatic Society called "The Vital Role of Affective Science in Medicine."
We will also continue to showcase other exciting formats, such as TED-style talks, salons, methods and speed networking events, flash talks, poster spotlights, and interactive poster sessions. Come see other invited speakers, including Marc Brackett, Cynthia Breazeal, Alan Fiske, Richard Lane, Jenn Lerner, Tali Sharot, and invited flash-talk speakers who will present groundbreaking research representing a wide range of affective science! There are also four exciting pre-conferences that will be held March 21.
Please see the conference website<https://t.e2ma.net/click/4fw8pd/824poyb/8ihu0q> for more information. You can register for SAS 2019 starting in November.
We're looking forward to seeing you in Boston for what promises to be another great SAS meeting!
Relevant Links
Check out our new look!<https://t.e2ma.net/click/4fw8pd/824poyb/obiu0q> We are extremely excited about the new Society website! It's been redesigned from the bottom up with clarity and effectiveness foremost in our minds. We hope affective scientists everywhere will find the site easy to navigate and use. Note that our members-only section will open soon.
www.facebook.com/affectScience<https://www.facebook.com/affectScience/>
twitter.com/affectScience<https://twitter.com/affectScience>
Dr. Rachael E. Jack, Ph.D.
Reader
Institute of Neuroscience & Psychology
School of Psychology
University of Glasgow
+44 (0) 141 5087
www.psy.gla.ac.uk/schools/psychology/staff/rachaeljack/
Multi-view Representations for Pose Invariant Face Recognition in Man and Machine
ESRC DTP Artificial Intelligence Studentship
School of Psychology and School of Computer Science, Nottingham University
This is a unique opportunity for a fully-funded ESRC Doctoral Studentship for applicants from the UK, EU or Overseas with a background in psychology, neuroscience, cognitive science, computer science or a related STEM discipline. The successful candidate will be located within the School of Psychology. The start date of this studentship may be 1st February 2019 or 1st October 2019 and will depend on the required award length (see ‘Award Lengths’ section below).
Pose-Invariant Face Recognition (PIFR) remains a significant stumbling block to realizing the full potential of face recognition as a passive biometric technology. This fundamental human ability poses a significant challenge for computer vision systems due to the immense within-class appearance variations caused by pose change, e.g., self-occlusion and coupled illumination or expression variations. Despite extensive efforts to solve the problem of pose-invariant face recognition it remains a significant barrier to developments in Artificial Intelligence. PIFR is achieved effortlessly by the human visual system but at present we do not understand the human system well enough to provide plausible solutions to the clear technological challenges. The aim of the studentship will be to enhance our understanding of how human observers achieve pose invariant recognition of faces in order to inform AI strategies. We will particularly focus on multi- view or pose-aware strategies and compare these against object-based models or pose-agnostic approaches. The work will involve both extensive psychophysical experimentation with human participants and computational experiments exploring computer models of pose-invariant dynamic face recognition. The project will be jointly supervised by Prof Alan Johnston (Psychology) and Dr Michel Valstar (Computer Science).
Award Lengths
The length of award offered will depend on the extent to which the candidate has met the ESRC’s core research methods training requirements. These are:
* Quantitative methods,
* Qualitative methods,
* Philosophy of Research and
* Research Design.
The extent to which you have met this criteria will be assessed during the application process. For those who have met all of the training, a +3 year award will be made, for those who have met some of the training, a 3.5 year award will be made, with a requirement that core training is completed within the first 12 months. If no core methods research has been undertaken by the candidate, then a +4 award will be made, which will include 180 credits research methods training before progressing to the PhD.
Owing to these requirements, +3 awards could start in February, but +4 awards would need to start at the beginning of the next academic year. +3.5 awards would depend on the type of training required and we will be able to advise candidates further prior to application if required.
You can read more about award lengths here: www.nottingham.ac.uk/esrc-dtc/mgs/dtp-training-<http://www.nottingham.ac.uk/esrc-dtc/mgs/dtp-training-> at-nottingham.aspx
Application Process
To be considered for this PhD, please complete the ESRC AI Studentship application form available online here with a covering letter and a CV as well as two references and then email this to christopher.atkinson(a)nottingham.ac.uk<mailto:christopher.atkinson@nottingham.ac.uk>.
Application deadline: Friday 9th November 2018 Midlands Graduate School ESRC DTP
The Midlands Graduate School is an accredited Economic and Social Research Council (ESRC) Doctoral Training Partnership (DTP). One of 14 such partnerships in the UK, the Midlands Graduate School is a collaboration between the University of Warwick, Aston University, University of Birmingham, University of Leicester, Loughborough University and the University of Nottingham.
Our ESRC studentships cover fees and maintenance stipend and extensive support for research training, as well as research activity support grants. For this priority area candidates ordinarily resident in an EU member state will be eligible for a full award as will candidates from overseas.
Informal enquiries about the research prior to application can be directed to: alan.johnston(a)nottingham.ac.uk<mailto:alan.johnston@nottingham.ac.uk>.
This message and any attachment are intended solely for the addressee
and may contain confidential information. If you have received this
message in error, please contact the sender and delete the email and
attachment.
Any views or opinions expressed by the author of this email do not
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where permitted by law.
We are seeking an enthusiastic PhD student with a particular interest in neuroscience of auditory (speech) perception. The PhD position is part of the Chair of Cognitive and Clinical Neuroscience led by Prof. Dr. Katharina von Kriegstein at the TU Dresden, Germany. The position is funded by the ERC-project SENSOCOM (http://cordis.europa.eu/project/rcn/199655_en.html).
The aim of the SENSOCOM project is to investigate the role of auditory and visual subcortical sensory structures in analysing human communication signals and to specify how their dysfunction contributes to human communication disorders such as developmental dyslexia. For examples of our work on these topics see von Kriegstein et al., 2008 Current Biology, Diaz et al., 2012 PNAS, Müller-Axt et al., 2017 Current Biology.
TU Dresden is one of eleven German Universities of Excellence and offers an interdisciplinary scientific environment. The Neuroimaging Centre at the TU Dresden (http://www.nic-tud.de) has cutting-edge infrastructure with 3-Tesla MRI, MRI compatible headphones and eye-tracking, several EEG systems, a neurostimulation unit including neuronavigation, TMS and tDCS devices.
The PhD position is available at the next possible date. Subject to personal qualification, employees are remunerated according to salary group E 13 TV-L 50%. There will be the opportunity to participate in the TU Dresden graduate academy (https://tu-dresden.de/ga?set_language=en).
For more information on the post please see the official advertisement: https://tinyurl.com/ybwe47bc
For more information on our research group see: https://tu-dresden.de/mn/psychologie/kknw
---
Katharina von Kriegstein
Professor of Cognitive and Clinical Neuroscience
Technische Universität Dresden
Bamberger Str. 7, 01187 Dresden, Germany
Phone +49 (0) 351-463-43145
https://tu-dresden.de/mn/psychologie/kknwhttps://twitter.com/kvonkriegstein