Details of the available positions for Post doc and Research Fellow call

1. Big Data and Distributed Systems; Distributed Computing research group, Professor Keijo Heljanko, Department of Computer Science and Engineering, Aalto University / HIIT.

We are looking for a postdoctoral researcher in Big Data and Distributed Systems. The research group specializes in design of parallel and distributed computing and their applications in processing large data sets in science and engineering. The group is involved both in practical applications involving design of distributed systems, as well as the formal underpinnings of design of distributed systems, including tool support for distributed systems design. Background in computer science in areas such as Big data, high performance computing, parallel computing, distributed systems, formal methods, databases, computer aided verification, machine learning, data mining, data science, and data analytics is considered an advantage.

 

2. Statistical Machine Learning, Professor Samuel Kaski, Helsinki Institute for Information Technology HIIT, Aalto University and University of Helsinki

We are looking for post docs for both theoretical and applied modeling work in statistical machine learning. We have excellent collaboration opportunities in computational biology, personalized medicine, brain imaging, human-computer interaction, information visualization and information retrieval. Regarding modeling, the keywords include probabilistic modelling, Bayesian inference and multiple data sources. We belong to the Finnish Center of Excellence in Computational Inference Research COIN and Biocentrum Helsinki. http://research.ics.aalto.fi/mi/

 

3. Machine learning for high-dimensional and structured data, Professor Hiroshi Mamitsuka, Professor Samuel Kaski, Helsinki Institute for Information Technology HIIT, Aalto University and University of Helsinki

We are looking for a postdoc who wants to develop new machine learning methods for high-dimensional and relational data. The work is part of a new project “Machine Learning for Augmented Science and Knowledge Work,” which gives unique application opportunities in personalized medicine, crop-breeding and information seeking. The project is part of Finland Distinguished Professor Programme (FiDiPro), a grant to create highly competitive research groups, lead by internationally merited researchers with top scientists in Finland. For more information about the PIs see http://www.bic.kyoto-u.ac.jp/pathway/mami/index.html and http://users.ics.aalto.fi/sami/, and on the FiDiPro at

http://www.tekes.fi/en/whats-going-on/news/tekes-fidipro-funding-brings-top-scientists-to-tampere-oulu-jyvaskyla-and-helsinki-/

 

4. Inference on intractable models and interactive intent modelling, Finnish Center of Excellence in Computational Inference Research COIN, Aalto University and University of Helsinki (contact persons: Professor Samuel Kaski, Professor Jukka Corander, research coordinator Maria Lindqvist)

We are looking for excellent postdocs to work in two flagships of COIN: 1. Inference on intractable models (for recent examples, see http://rspb.royalsocietypublishing.org/content/281/1794/20141324 and http://arxiv.org/abs/1501.03291) and 2. interactive intent modelling (for a recent example see https://www.hiit.fi/node/3079). Joint affiliations among the 6 research groups of COIN are encouraged. COIN's objective in general is to bring together several of the different core fields of expertise, to push the boundaries of what is possible in inference. Outstanding applicants interested in other aspects of machine learning, statistical inference, logical inference and their applications are welcome as well. For more information, including our recent flagship publications in PNAS and Nature journals, see http://research.ics.aalto.fi/coin/

 

5. Complex Systems Computation Research Group (CoSCo), Professor Petri Myllymäki, Department of Computer Science & HIIT, University of Helsinki.

CoSCo is a member of the Finnish Centre of Excellence in Computational Inference Research (COIN), and we are looking for candidates with a strong background and interest in machine learning, probabilistic modelling or big data issues in general, or in one of our four focus areas: Adaptive Computing (led by Patrik Floréen), Constraint Reasoning and Optimization (Matti Järvisalo), Multi-Source Probabilistic Inference (Arto Klami) and Information, Complexity and Learning (Teemu Roos). For more information, please visit http://www.hiit.fi/cosco/

 

6. Machine Learning for Structured Domains, Professor Juho Rousu, Helsinki Institute for Information Technology HIIT, Department of Computer Science, Aalto University.

 The KEPACO research group (http://research.ics.aalto.fi/kepaco/)led by prof. Rousu develops advanced machine learning methods and tools for data science. The group specialises on kernels and regularised learning in structured domains: structured data (sequences, trees, graphs), multiple and structured outputs, multiple views and ensembles. Big data applications in molecular biology provide a rich source of machine learning problems for our methods. We are looking for a post-doctoral researcher to join our team. Applicants with strong machine learning background and experience in one or more of the above topics are encouraged to apply.

 

7. Multimodal and adaptive interaction, interactive visualization, Professor Giulio Jacucci, Department of Computer Science & HIIT, University of Helsinki.

Ubiquitous Interaction is a HCI group at HIIT lead by professor Giulio Jacucci specialising in multimodal, adaptive, persuasive interaction and interactive visualisation and information retrieval. The group has an exciting range of platforms and tools such as large interactive walls, physiological computing, wearable haptics and more. The group is highly multidisciplinary including design, social psychology, electronics, information visualisation and retrieval.

 

8. Augmented research, Multiple research groups at Helsinki Institute for Information Technology HIIT, Aalto University and University of Helsinki. (Contact person: coordinator of this focus area, Dr Markus Koskela)

The HIIT-wide focus area about augmented research (see http://augmentedresearch.hiit.fi/) is a big multidisciplinary activity spanning several research groups of Helsinki Institute for Information Technology HIIT at Aalto University and University of Helsinki. Our goal is to improve the process of doing research by IT. We have started by bringing humans in the information exploration loop by combining human-computer interaction and machine learning. Initiatives on how you could contribute as a postdoc or research fellow are welcome. More information at http://augmentedresearch.hiit.fi

 


Last updated on 25 Mar 2015 by Anne Peltola - Page created on 11 Sep 2014 by Helena Knuuttila