Large number of postdocs in Finland

Job Description:
1. Automated linguistic analysis and creativity, Professor Hannu Toivonen, Department of Computer Science & Helsinki Institute of Information Technology, University of Helsinki The Discovery research group carries out research in the areas of computational creativity and data mining. We are now looking for a postdoc to join our two projects related to linguistic analysis and creativity, both funded by the Academy of Finland. The ideal candidate will have a strong background in computer science as well as in language technology or linguistics, and a keen interest into computational creativity. For more information, please visit Discovery research group: http://www.cs.helsinki.fi/en/discovery   2.  Genome-scale algorithmics, Professor Veli Mäkinen, Department of Computer Science & Helsinki Institute of Information Technology, University of Helsinki Genome-scale algorithmics research group develops algorithms and data structures for the analysis of genome-scale data. Such data is abundant due to modern molecular biology measurement techniques like high-throughput sequencing. We are especially interested in applications of compressed data structures. We are looking for a postdoc to bring new expertise in our current research areas such as pan-genome indexing, time- and space-optimal sequence analysis, and genome and transcript assembly. For more information, please visit Genome-scale algorithmics : www.cs.helsinki.fi/gsa   3. Complex Systems Computation Research Group, Professor Petri Myllymäki, Department of Computer Science & Helsinki Institute of Information Technology, 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, and/or in one of our four focus areas:

• Constraint Reasoning and Optimization (led by Matti Järvisalo),
• Information, Complexity and Learning (led by Teemu Roos),
• Intelligent Interactive Information Access (led by Patrik Floréen) and
• Multi-Source Probabilistic Inference (led by Arto Klami).

For more information, please visit Complex Systems Computation Research Group http://www.hiit.fi/cosco/   4. Probabilistic programming for data analytics, Academy Research Fellow  Arto Klami, Department of Computer Science & Helsinki Institute of Information Technology, University of Helsinki We are looking for a postdoc to work on probabilistic programming, in particular for developing black-box variational inference methods for complex probabilistic models. The goal is to build computationally efficient models that meet the demands of practical data analysis tasks, scaling up to large amounts of data and supporting streaming data. The project combines fundamental basic research with industry collaboration and opportunity to contribute to open-source software development. The candidate should have a strong track record in conducting research in machine learning and probabilistic modelling, ideally having also previous experience with variational inference methods. For more information, please visit: https://www.hiit.fi/cosco/mupi   5. Constraints, Satisfiability, and Optimization (1-2 postdoctoral position), Dr. Matti Jarvisalo, Department of Computer Science & Helsinki Institute of Information Technology, University of Helsinki We are looking for talented and highly motivated individuals with background in applied and/or theoretical aspects of constraints, computational logic, and/or discrete optimization. Earlier experience and a track record, witnessed by publications in well-known journals and/or conferences, in SAT, constraint programming (CP), integer programming (MIP), answer set programming (ASP), satisfiability modulo theories (SMT), or related areas of research are expected. Possible research topics include (but are not restricted to):

• state-of-the-art constraint solving techniques for problems beyond NP;
• application-specific constraint-based approaches to AI applications such as computational
• argumentation, computational social choice, machine learning;
•  analysis of Boolean constraint solving techniques and their underlying proof systems;
• exact model counting; parallel constraint solving.

For more information, please visit: The Constraint Reasoning and Optimization group: http://www.hiit.fi/cosco/coreo/   6. Digital Health & Data-Driven Healthcare (1-3 postdoctoral positions), Professors Tero Aittokallio,  Samuel Kaski,  Juho Rousu, Department of Computer Science & Helsinki Institute of Information Technology & Institute for Molecular Medicine Finland, University of Helsinki & Aalto University We are looking for several post-doctoral researchers to work on machine learning and computational modelling problems arising in Digital Health and Data-Driven Healthcare, related to new large research initiatives in Health&Wellbeing research in the Helsinki region. The positions allow combining state-of-the-art computational methods with large-real world data arising in healthcare and personalized medicine, analysed in collaboration with experts from Aalto University, University of Helsinki, Hospital District of Helsinki and Uusimaa (HUS) as well as  Institute for Molecular Medicine Finland (FIMM). We expect the applicants to have a PhD degree (or close to completing one) in computer science, mathematics or statistics, with an excellent publication record. We expect solid research experience in one or more of the following fields:

• Heterogeneous, multi-view and structured data analytics
•  Human-computer interaction
•  Large-scale analysis of omics data
•  Large-scale optimisation
• Probabilistic modelling and Bayesian statistics
•  Regularized learning and kernel methods

Experience in bioinformatics and systems biology, or healthcare data processing will be considered an asset.   7. Postdoctoral Researcher in Theory of Distributed Computing, Professor Jukka Suomela, Department of Computer Science, Aalto University The postdoctoral researcher will take part in the project "Charting the Landscape of Distributed Time Complexity", funded by the Academy of Finland for 2015-2019. The project is related to the theoretical foundations of distributed computing, with the main focus on understanding the distributed time complexity of so-called local coordination problems. For more information on our research team and the research area, please visit our web page http://research.ics.aalto.fi/da/   8. Probabilstic Machine Learning (1-3 postdocs or research fellows), Professor Samuel Kaski, Helsinki Institute for Information Technology HIIT, Department of Computer Science, Aalto University We are looking for postdocs or research fellows interested in probabilistic modelling and machine learning, both theory and applications. Candidates interested in some subset of the following are particularly welcome: Bayesian inference, multiple data sources, prior elicitation, differential privacy, ABC, retrieval of relevant data. Strong application areas with excellent collaboration opportunities are: personalized medicine, bioinformatics, user interaction, brain signal analysis, information visualization and intelligent information access.  We belong to the Finnish Center of Excellence in Computational Inference Research COIN. http://research.cs.aalto.fi/pml   9. Inference (1-3 postdocs or research fellows), Professor Samuel Kaski, Professor Jukka Corander, Finnish Center of Excellence in Computational Inference Research COIN, Aalto University & University of Helsinki We are looking for excellent postdocs to work in COIN, in particular its two recent spearhead topics: 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/   10. Machine learning for high-dimensional and structured data (1-2 postdocs), Professor Hiroshi Mamitsuka, Professor Samuel Kaski, Helsinki Institute for Information Technology HIIT, Department of Computer Science, Aalto University 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 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 please see:

•  http://www.bic.kyoto-u.ac.jp/pathway/mami/index.html and
•  http://users.ics.aalto.fi/sami/, and
• on the FiDiPro athttp://www.tekes.fi/en/whats-going-on/news/tekes-fidipro-funding-brings-top-scientists-to-tampere-oulu-jyvaskyla-and-helsinki-/

  11. Network inference, Professor Aristides Gionis, Department of Computer Science & Helsinki Institute of Information Technology, Aalto University The objective of this project is to develop novel computational methods for network-inference problems. We consider settings in which we observe the behavior of groups of entities and the goal is to infer the structure of an underlying hidden network. We will explore different problem variants with increasing complexity, richness, and ability to model real-world application scenarios. Successful applicants are expected to have an excellent research track record in data mining, machine learning, and/or combinatorial optimization. For more information please see: Data mining group, Aalto University: http://research.ics.aalto.fi/dmg/

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Requeriments :

• Doctorate Degree

Skills :

• Bioinformatics
• Biology
• Computational Biology
• Dynamical Systems
• Genome Assembly
• Information Theory
• Machine Learning
• Modeling
• Next Generation Sequencing
• Programing Skills
• Statistics

Areas :

• Bioinformatics
• Computational Biology
• Systems Biology

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Additional Info: