Post-doc position combining machine learning with affective neuroscience, neuroimaging, and human activity measurements

A post-doc position combining machine learning with affective neuroscience, neuroimaging, and human activity measurements is available at Aapo Hyvarinen's research group at the Department of Computer Science of the University of Helsinki, Finland. The position is part of the project
"Next generation affective life log: Machine learning with multimodal sensor networks"
The goal of the project is to obtain information on a person's affective state (emotions, mood) using non-invasive measurements including brain imaging (EEG, fNIRS), body motion (Kinect etc.), psychophysiology, and other measurement modalities. Such affective information will be used for health-care and nursing purposes, e.g. for elderly people. Measurements are carried out in a dedicated house in which residents can be monitored during everyday life, including wearable brain imaging instruments.
The project is in collaboration with Motoaki Kawanabe at ATR, a leading research institute at the cross-roads of machine learning and neuroscience. Long-term research visits to ATR in Japan (near Kyoto) are anticipated in the project, as the dedicated house and data collection are at ATR.
The candidate should have an excellent PhD and publication record in machine learning, data science or related field, preferably with some experience in neural or human data analysis. Neuroscience/psychology PhD's with a very quantitative (methods) orientation can also be considered, as well as candidates who are likely to get a PhD within the next few months.
The starting data is preferably 1 September 2015, but this is flexible. The duration is to be negotiated, by default starting by one year with possible extensions.
The review of applications will start on May 6th and will continue until the position is filled. Please send applications and enquiries to aapo.hyvarinen-AT-helsinki.fi, attaching (max size 5MB): CV, publication list, short statement of research interests, and names and email addresses of 2-3 people willing to give their opinion on your competence.