Several Postdoctoral Researcher and Research Fellow Positions in ICT

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.

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

Positions are available in the following areas: (Please indicate in your application the number of the area you are interested in, and give motivations for your selections.) NB! New positions might be added at a later stage.

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. Foundations of Computational Health, Juho Rousu, Aristides Gionis, Keijo Heljanko, Jari Saramäki (Aalto University), Tero Aittokallio, Ville Mustonen (University of Helsinki). NB! Up to 4 positions available.

Foundations of Computational Health Research programme of Helsinki institute for Information Technology HIIT is looking for several post-doctoral researchers to work on cutting-edge technologies for Computational Health. 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

* Big Data Frameworks for genome-scale algorithmics
* Complex networks modelling and mining
* Computational metabolomics
* Machine learning on structured big data
* Modelling drug resistance
* Network pharmacology modelling

For more information on our research, please visit: Juho RousuTero 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:

5. High-throughput bioinformatics and epigenomics, Prof. Harri Lähdesmäki

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 in mammalian cells using a variety of next generation sequencing data, with emphasis on chromatin accessibility, different oxidized DNA methylation modifications, chromatin looping and other data. 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 molecular biology research groups. For more information, see ( or contact Harri Lähdesmäki (

6. 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) technology in the computational logic group. The candidates of interest have PhD in Computer Science, with a major subject relevant to computational logic such as knowledge representation and reasoning, constraint programming, Boolean modeling and optimization, automated reasoning. Moreover, we expect comprehensive background knowledge in ASP and a track record on implementing solver technology that is confirmed by scientific publications and existing, preferably public domain software.  Strong skills at programming languages (such as C, C++, Python, ML, Haskell used in solver development) are important. Contact:

For more information on our research, please visit:

7. 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 HIIT, 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 a postdoc to join us to explore methodological foundations for co-adaptative interactive systems. The postdoc 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 searching for a postdoc to work on either or both of 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: 

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

We are looking for an excellent postdoc or research fellow to the Probabilistc Machine Learning group. We work particularly on Bayesian inference in challenging conditions: multiple data sources, small sample sizes, with parallelization, interatively, preserving privacy, likelihood-free, and/or for nonparametric or semiparametric (read: Bayesian deep learning) nonlinear models. Get in touch about details!

For more information on our research, please visit:

9. 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:

10. 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.

Additional information on our research is available at and (

11. New language modeling methods for video subtitling and foreign language learning, Mikko Kurimo, Aalto University, Department of Signal Processing and Acoustics,

We are developing video and online subtitling methods for hearing impaired and language learners as well as fully speech-based language learning methods. Knowledge of speech and language processing and machine learning as well as all programming skills are valuable.  Because this is a large project and we already have experts in different areas, it will be possible to adjust the content of the work according to the candidate's interests and skills.

12. 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

13. Creatively self-adaptive software architectures, Prof. Hannu Toivonen and Prof. Tomi Männistö
University of Helsinki, Department of Computer Science

We are starting new, exciting research in the intersection between computational creativity and self-adaptive software, with the goal of developing novel software architectures that can creatively adapt themselves in unforeseen situations. We are looking for a postdoc with a background in software architectures or computational creativity and a strong interest to also learn the other one. 

The position is exceptionally located in two research groups and has access to a variety of expertise:
- The Discovery group of Prof. Hannu Toivonen (computational creativity) 
- The Empirical Software Engineering group of Prof. Tomi Männistö

For more information about past work of the two research groups, see the above links.

14. Big Data Management, Prof. Jiaheng Lu, Department of Computer Science, University of Helsinki

As more businesses realized that data, in all forms and sizes, is critical to making the best possible decisions, we see the continued growth of database systems that support massive volume of non relational or unstructured forms of data. 

We are looking for a postdoctoral researcher in the broad area of NoSQL database. Candidates should have a solid background in big data management and database. A good publication record in the field of database is expected.    

For more information on our research, please visit:

Sunday, March 19, 2017
Employing university: 
Aalto University
University of Helsinki

Last updated on 3 Mar 2017 by Stefan Ehrstedt - Page created on 17 Feb 2017 by Stefan Ehrstedt