** Aalto University and University of Helsinki, the two leading

universities in Finland within computer science, are looking for two

postdocs at the intersection of Human-Computer Interaction and Machine

Learning **

We are three groups starting new exciting research at the intersection of

machine learning, computational statistics, and human-computer

interaction. We are looking for two postdocs to join us to explore

methodological foundations for co-adaptative interactive systems. The

postdocs will participate in research that establishes the technical

principles that allow choosing the optimum adaptation for an individual by

anticipating how she will react and adjust to the change, taking into

account personal capabilities, knowledge, and behavioral strategies. On

the other hand, co-adaptation is an intriguingly challenging probabilistic

inference problem, which requires developing new Approximate Bayesian

Computation techniques. The objective of co-adaptation is not only to

improve the fluency of computer use but to boost success rate, efficiency,

enjoyability, and capabilities in knowledge-intensive tasks. We are

seeking to fill postdoc positions on two core topics:

1. Learning user models from interactive behavior: inferring parameters,

constraints, and strategies of a user by fitting to log data a model of a

user who plans and optimizes. Probabilistic modelling and Approximate

Bayesian Computation (ABC) are keywords.

2. Model-based user interface adaptation: Machine learning and

optimization methods to decide in real time the timing and type of UI

adaptations.

We expect the applicants to have a PhD degree (or close to completing one)

in machine learning, computational statistics, human-computer interaction,

neurosciences, visualization, or operations research, with an excellent

publication record.

The deadline for sending the application is September 30, 2016, at 2pm

Finnish time.

For the full call text and information about the application process,

please visit: