Aapo Hyvärinen

Menu

New

AISTATS2010: Noise-contrastive estimation: A new estimation principle for unnormalized statistical models

NeuroImage: Independent component analysis of short-time Fourier transforms for spontaneous EEG/MEG analysis

TopiCS: Statistical models of natural images and cortical visual representation. (invited review)

ICANN2009: Learning features by contrasting natural images with noise

ICANN2009: Modelling image complexity by independent component analysis, with application to content-based image retrieval

UAI2009: A direct method for estimating a causal ordering in a linear non-Gaussian acyclic model

UAI2009: On the Identifiability of the Post-Nonlinear Causal Model

Post-doc positions in brain imaging signal analysis

Applications are invited for

Two postdoctoral positions

in the project "Computational analysis of complex brain imaging data" in Helsinki, Finland. This is a joint project with Aapo Hyvarinen (Univ of Helsinki) and Riitta Hari (Aalto University, formerly called Helsinki Univ of Technology).

The postdoctoral training consists of developing new models, methods, and paradigms for brain imaging experiments using MEG and EEG. Almost all brain imaging data are currently analyzed by simple methods which constrain the experiments to simple laboratory situations. We develop new methods with which we can analyze brain activity in situations closer to everyday-life. An important example is the setting of two-person neuroscience, in which two subjects are in social interaction with each other, while both of their brains are scanned. Another example is when the subject is in resting state and we only observe the internal dynamics of the brain.

One of the post-doc positions has a more computational-mathematical orientation and is concentrated on development of new data analysis methods for MEG and EEG. It is located in Hyvarinen's group at the University of Helsinki, which is one of the world's leading groups in unsupervised machine learning and its applications in neuroscience. The other position combines experimental work with methods development and is in Hari's group at the Brain Research Unit of the Aalto University (Helsinki University of Technology), well-known world-wide for its work in the development of MEG. The selected candidates will receive world-class post-doctoral training in a highly multidisciplinary and paradigm-shifting project.

Applications from candidates with a PhD degree in computer science, neuroscience, statistics, psychology, signal processing, or similar, are welcome. Candidates with experience in neuroscience are preferred but exceptionally strong candidates with a strong future commitment to neuroscience are also eligible. Candidates who are likely to obtain a PhD degree in the next few months can also apply. The starting date and the duration are flexible.

Please send your application to: aapo.hyvarinen [at] helsinki.fi . Attach at least: 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. Review of applications will start on 15th February 2010 and continue until the positions are filled.