20 Postdoctoral Researcher and Research Fellow Positions in ICT (Helsinki, Finland)

 
 
Aalto University and the University of Helsinki, the two leading universities in Finland in computer science and information technology, are currently looking for several Postdoctoral Researchers or Research Fellows in ICT. Some of the positions are placed in the new research programmes of the Helsinki Institute for Information Technology HIIT, which is a joint research institute of Aalto University and the University of Helsinki for basic and applied research in information technology. Positions are avalable in the areas listed below (please indicate in your application the number of the area you are interested in). For the full call text and information about the application process, please visit https://www.hiit.fi/openpositions/Fall2016.
 

Positions are avalable in the following areas:

(Please indicate in your application the areas you are interested in, and give motivations for your selections.)

 

1. HIIT Research Programme on Computational Inference programme (COIN), Professors Samuel Kaski, Jukka Corander, Petri Myllyma╠łki, Antti Oulasvirta, Matti Pirinen, Aki Vehtari

COIN is a research programme in machine learning and probabilistic modelling, which are core technologies of data science. Our main focus is on the new methods required for the interrelated challenges of interactive modelling, computational interface design, and precision medicine. Additional keywords: Approximate Bayesian computation, evolutionary epidemiology, multiple data sources, probabilistic programming.

For more information on our research, please visit: Samuel Kaski, Jukka Corander, Petri Myllymäki, Antti Oulasvirta, Matti Pirinen, Aki Vehtari

 

2. HIIT Research Programme on Foundations of Computational Health (FCHealth), Professors Juho Rousu, Veli Mäkinen, Tero Aittokallio, Aristides Gionis, Keijo Heljanko, Jari Saramäki

FCHealth programme aims to solve hard computational challenges faced upon the emerging digitalization and wide adoption of data-driven approaches in healthcare. 

We are looking for several post-doctoral researchers to work on cutting-edge technologies for Computational Health, related to a new research programme in Helsinki Institute for Information Technology and ongoing large initiatives in Data-Driven Healthcare 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, bioinformatics, biomathematics, biostatistics, statistical physics, or a related field, with an excellent publication record. We expect solid research experience  in one or more of the following fields:  Analysis of high-throughput omics datasets, Complex networks modelling and mining, Computational metabolomics, Genome-scale algorithmics, Machine learning on structured big data, Modelling drug resistance, Network pharmacology modelling

For more information on our research, please visit: Juho RousuVeli MäkinenTero Aittokallio, Aristides Gionis, Keijo Heljanko, Jari Saramäki 

 

3. HIIT Research Programme on Building Trust in Secure Computing Systems (BURST), Professors Tuomas Aura, N. Asokan, Valtteri Niemi, Stavros Tripakis,  Sasu Tarkoma
BURST program starts from the observation that, while digitalization is pervasive, computing systems are still inherently vulnerable. Our objective is to build trust in computing systems and make the underlying platforms verifiable at all stages of lifecycle: design, build, deployment, and also run-time. The approach of BURST is to leverage collective expertise of PIs for achieving build-in pervasive verifiability, combining work in authentication (Aura), attestation (Asokan), cryptographic proofs (Niemi), formal verification (Tripakis),  and network/protocol security (Tarkoma). The long-term mission of BURST program, aiming towards the year 2025, is to enable the design, building and deployment of distributed large-scale systems where each node (component, device, network element etc.) contributes in verifying trustworthiness of the entire system. Each node would also be able to verify whether any other node or even the entire system is trustworthy. 
 
For more information on our research, please visit: Tuomas AuraN. AsokanValtteri NiemiStavros TripakisSasu Tarkoma
 
4. HIIT Research Programme on Augmented Research (AR), Professors Giulio Jacucci, Samuel Kaski, Petri Myllymäki, Aristides Gionis, Sasu Tarkoma, Niklas Ravaja
Augmented search, research, and knowledge work are the main themes of the multidisciplinary HIIT-wide research initiative that is a strategic research focus of HIIT. Several research groups ranging from Human-Computer Interaction to Machine Learning and Complex Systems Computation collaborate to produce cutting edge research and demonstrations. The project investigates how Human- Computer Interaction and Probabilistic Machine Learning can be combined increase, by order of magnitude, the effectiveness of search and knowledge work. 
 
We are looking for postdoctoral researcher for information retrieval and machine learning.The research  investigates methods and tools to better utilize the massive explosion of raw data, documents, distributed information and link structures between these, and sensory information recorded from the users. The methods and pilot applications are expected to revolutionize our work practices in data- driven fields such as modern biology, business intelligence, and others. The work will be based on developing novel interactive retrieval and information exploration methods.  Moreover the position will give the opportunity develop a platform for comparing methods for the wider community also organising open competitions. 
 
For more information on our research, please visit: http://augmentedresearch.hiit.fi/
 
5. Information Retrieval, Human-Computer Interaction HCI, Machine Learning,  Professor Giulio Jacucci , University of Helsinki

Ubiquitous Interaction a HCI group at HIIT is lead by professor Giulio Jacucci specialising in multimodal, adaptive, persuasive interaction and interactive visualisation and information retrieval. The group is highly multidisciplinary including members from information visualisation, design, cognitive science, electronics, and information retrieval, and has an exciting range of platforms and tools such as large interactive walls, physiological computing, wearable haptics and more.  Recently important work included providing several interactive visualisation for exploratory search.

The position is in the intersection of  Information Retrieval IR, and Human-Computer Interaction HCI , and machine learning. The aim is to investigate novel approaches that combine search and recommendation.

For more information on our research, please visit:https://scholar.google.fi/citations?hl=en&user=cmpzu9sAAAAJ&view_op=list_works&sortby=pubdate

 

6. Adaptive and immersive environments for augmented social interaction,  Professor Giulio Jacucci , University of Helsinki

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

The position is in the intersection of immersive virtual environments and physiological computing, investigating implicit physiological interaction, haptics and virtual environments in HMD for augmenting social interaction in decision making, meditation and more. 

For more information on our research, please visit:https://scholar.google.fi/citations?hl=en&user=cmpzu9sAAAAJ&view_op=list_works&sortby=pubdate

 

7. 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/

 

8. Internet of Things, Mario Di Francesco, Department of Computer Science, Aalto University

We are looking for a postdoctoral researcher in the broad area of the Internet of Things. Candidates should have a solid background in networking, with core expertise on algorithm design and analysis, systems research, network optimization, human-computer interactions or security.

For more information on our research, please visit: https://users.aalto.fi/~difram1/

 

9. Creative software: automated text generation, adaptive software architectures, Professor Hannu Toivonen & Professor Tomi Männistö, Department of Computer Science, 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 interested either in linguistic analysis and creativity, with applications e.g. in automation of news production, or in (creatively) self-adaptive software architectures. The ideal candidate will have a strong background in computer science complemented with knowledge of either language technology or software architectures, and a keen interest into computational creativity.


For more information, please visit Discovery research group: https://www.cs.helsinki.fi/en/discovery

 

10. Machine Learning and Adaptive User Interfaces, Professor Antti Oulasvirta, Department of Communications and Networking, Aalto University; Professor Jukka Corander, Department of Mathematics and Statistics,  University of Helsinki; Professor Samuel Kaski, Department of Computer Science & Helsinki Institute of Information Technology, Aalto University

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 cutting-edge 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 remarkably 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. 

For more information, please email the PIs or visit the group pages: http://userinterfaces.aalto.fi/http://research.cs.aalto.fi/pml/http://www.helsinki.fi/bsg/ 

 

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

We are looking for 2 postdocs or research fellows to work on probabilistic machine learning, in particular Bayesian inference in challenging conditions: multiple data sources, small sample sizes, with parallelization, interatively, preserving privacy, likelihood-free, and/or for nonparametric nonlinear models. The work is done in collaboration with other machine learning and statistics researchers within the group, with other groups of the Center of Excellence on Computational Inference Research COIN, and with top-level collaborating groups in medicine, user interaction and neuroscience. 


For more information on our research, please visit: http://research.cs.aalto.fi/pml/

12. Probabilistic machine learning for precision medicine and data-driven healthcare, Professor Samuel Kaski, Helsinki Institute for Information Technology HIIT, Aalto University and University of Helsinki

We are looking for a postdoc who wants to participate in developing the new probabilistic modelling and machine learning methods needed for genomics-based precision medicine and predictive modelling based on clinical data. Suitable candidates have either a strong background in machine learning and a keen interest to work with top-level medical collaborators to solve these profound medical problems, or strong background in computational biology and medicine, and a keen interest to develop new solutions by working with the probabilistic modelling researchers of the group.

For more information on our research, please visit: http://research.cs.aalto.fi/pml/

 

13. Machine learning for high-dimensional and structured data, 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:

 

14. Solver technology for answer-set programming, Professor Ilkka Niemelä and Dr. Tomi Janhunen Department of Computer Science Aalto University

We are seeking for a postdoctoral researcher to continue the development of answer-set programming (ASP) solver technology in the computational logic group.

The candidates of interest have PhD in Computer Science, with a major subject relevant to computational logic (knowledge representation and reasoning, constraint programming, automated reasoning). Moreover, we expect comprehensive background knowledge in ASP and a track record on implementing similar solver technology that is confirmed by scientific publications and existing, preferably public domain software.  Strong skills at programming languages (such as C, C++, Python, SML, Haskell used in solver development) are essential.  We consider previous experience in ASP, PROLOG, and constraints as an asset.

For more information on our research, please visit: https://research.ics.aalto.fi/cl/

 

15. High-throughput bioinformatics and regulatory genomics, Prof. Harri Lähdesmäki, Department of Computer Science, Aalto University

We are looking for a postdoc to work in our Computational Systems Biology research group to develop computational and statistical methods for high-throughput bioinformatics and regulatory genomics. The goal of this project is to reveal transcriptional and epigenetic mechanisms of cell differentiation in mammalian cells using a variety of next generation sequencing data, with emphasis on chromatin accessibility, different oxidized DNA methylation modifications, chromatin looping and histone modification data as well as single-cell technologies. Applicants are expected to have background in bioinformatics, computational biology, probabilistic modeling or machine learning, with keen interest in molecular biology. Postdoc will be responsible for developing and applying efficient computational biology methods and collaborate with experimental and molecular biology research groups.

For more information, see (http://research.ics.aalto.fi/csb/) or contact Harri Lähdesmäki (harri.lahdesmaki@aalto.fi).

 

16. Probabilistic modeling for biomedicine and personalised medicine, Prof. Harri Lähdesmäki, Department of Computer Science, Aalto University

We are looking for a postdoc to work in our Computational Systems Biology research group to develop computational and statistical methods for biomarker discovery and personalized medicine. This project builds on large-scale data sources obtained by profiling individuals over time and collecting various -omics time series data, including e.g.transcriptome, proteome, microbiome, and methylome. Postdoc will be responsible for developing and applying various probabilistic and machine learning methods to identify trait associated biomarkers and to develop novel statistical tools for personalised medicine. Applicants are expected to have background in probabilistic modeling, statistics or machine learning with keen interest in bioinformatics and molecular biology.

For more information, see (http://research.ics.aalto.fi/csb/) or contact Harri Lähdesmäki (harri.lahdesmaki@aalto.fi)

 
17. Mobile Computing and Systems, Prof. Antti Ylä-Jääski & Dr. Matti Siekkinen, Department of Computer Science, Aalto University
The research group is looking for 1-2 postdoctoral researchers to work on mobile multimedia computing with applications to, for instance, video streaming and gaming. The main focus of the research is modeling and optimization of Quality of Experience, in particular in latency-sensitive services and applications.
 

 


Last updated on 12 Sep 2016 by Ida Salin - Page created on 14 Aug 2015 by Anne Peltola