The position is located in the Statistical Machine Learning and Bioinformatics research group at the Department. The group is part of Helsinki Institute for Information Technology HIIT in Aalto University. The work will be supervised by the principal investigator of the project, academy research fellow Jaakko Peltonen. The work involves collaboration with Finnish researchers including members of the Statistical Machine Learning and Bioinformatics research group led by Prof. Samuel Kaski, and international researchers from the UK, Belgium, and the USA. The research site is located on the Aalto University campus in Otaniemi, a short bus ride away from the centre of Finland`s capital Helsinki.
- Applicant must have a MSc degree in computer science, electrical engineering, mathematics, physics, or a related field. It is also possible to start as a research assistant working on one`s Master`s thesis.
- A strong mathematical background and an interest in probabilistic modeling and/or machine learning are necessary.
- An interest in some of the following topics is essential: dimensionality reduction, manifold learning, visualization, and multi-task learning. Experience in these topics is an advantage.
- A strong study record and strong track record in research are advantages.
- Good programming skills in languages such as C/C++/Matlab/R/Python and good written and spoken communication skills are desired.
The salary will be determined based on the Aalto University salary system (2200-3200 euro per month before tax for a doctoral student depending on qualifications and performance). The initial appointment will be for one year. Extension will be possible depending on the availability of funding.
How to apply
The application materials must include:
- a curriculum vitae
- a copy of study records
- contact details of at least two references
- and any other materials deemed relevant
For more information:
To contact academy research fellow Jaakko Peltonen or HR Coordinator Stefan Ehrstedt. E-mail: firstname.lastname@example.org
Deadline: 31 October 2011
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