Projects recruiting

The participating units of HICT have currently 15 fully funded positions available for exceptional doctoral students. In this call you can either apply to a research group in general, or/and to a specific research project. The group descriptions can be found through the list of HICT supervisors at "".

The call-specific projects are:


  • Computational Methods and Optimization for User Interface Design (Prof. Antti Oulasvirta)

    We are a new, vibrant multidisciplinary group working in the area of user interfaces. Unique to our work is that we formulate user interface problems formally in order to approach them with computational methods. There are plenty of exciting opportities in HCI to apply computational methods. They help us find exploitable structure in human behavior, solve really large design problems etc. In Spring 2016, we are looking for an exceptionally good computer science student trained in any of the following areas: modeling, optimization, or information visualization. Please see our group page for examples and more information:


  • One position to be funded by the Academy of Finland project "Network structure from group response (NESTOR)" (Prof. Aristides Gionis)

    The project focuses on network-inference problems. The objective is to reconstruct hidden structure of networks from the observed behavior of different groups. Emphasis will be given to both theoretical formulations and real-world applications. A successful applicant should be interested and have some familiarity with graph mining, combinatorial optimization, and/or machine learning.


  • Complex Systems Computation (Prof. Petri Myllymäki)

    The CoSCo research group 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:  Intelligent Interactive Information Access (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
  • Probabilistic machine learning (Prof. Samuel Kaski)

    We are looking for PhD candidates 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. The group has several excellent postdocs who participate in supervision. We belong to the Finnish Center of Excellence in Computational Inference Research COIN.


  • Machine learning for personalized medicine (Prof. Samuel Kaski)

    We are looking for PhD candidates interested in probabilistic modeling and machine learning applied to personalized medicine and digital health. The goal is to develop methods for so-called precision or personalized medicine, for choosing treatments according to genetic and other information of the patient. The work is done with medical and human computer interaction experts from Institute for Molecular Medicine Finland FIMM and University College London, UK. We belong to the Finnish Center of Excellence in Computational Inference Research COIN and Biocentrum Helsinki.
  • Machine learning for high-dimensional and structured data (Prof. Hiroshi Mamitsuka and Prof. Samuel Kaski)

    We are looking for a PhD candidate 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 about the PIs see and, and on the FiDiPro at
  • Construction and Classification of Discrete Mathematical Structures (Prof. Patric Ostergard)

    The team has an open position for a PhD candidate with a background in algorithms and discrete mathematics. In this project, existence and classification of combinatorial structures are considered. The techniques are mainly computational, typically involving (NP-)hard subproblems such as finding cliques in graphs, but also algebraic and combinatorial methods play a central role. The structures considered include codes, designs, graphs, and (Hadamard) matrices.
  • Advanced constraint solvers and their applications (Prof. Ilkka Niemelä)

    We are looking for highly talented doctoral students who have previous knowledge of constraint-based techniques such as Boolean satisfiability (SAT), satisfiability modulo theories (SMT), and answer-set programming (ASP). The research topics will be related to the development of new kinds of language extensions, translators, and solvers as well as applying them to challenging computational problems arising in the areas of computer-aided verification, AI planning, diagnosis, machine learning, statistical inference etc. We expect strong programming skills from candidates of interest. Candidates with previous knowledge in the application areas mentioned above are also encouraged to apply. Contact persons: Docent Tomi Janhunen and Docent Tommi Junttila, Department of Computer Science, Aalto University. See further group information at


  • EMERGENT (Excellent Mobile Experience through Flexible Access (Prof. Heikki Hämmäinen)

    EMERGENT project develops wireless multi-access (multihoming) solutions for commercial and public safety purposes. The main objective is to improve the availability and quality (QoS/QoE) of mobile services by extending from single-access to multi-access architecture. The thesis topic deals with multi-access QoE, business roles, value networks and pricing structures which are analyzed using techno-economic methods. The possible research viewpoints can a) emergency services, b) low-cost Internet in developing countries, c) disruptive changes in communication architectures and ecosystems. Link to further information:
  • Machine Learning for Computational Metabolomics (Prof. Juho Rousu)

    The KEPACO research group group develops machine learning methods, models and tools for biomedicine and digital health.  We currently looking for excellent PhD candidates to conduct research on computational metabolomics, including the identification, function, interactions and bioactivity of small molecules such as metabolites or drugs. The focus of the PhD project can be flexibly chosen in between machine learning methods development and the biomedical applications.
  • Automated linguistic analysis and creativity (Prof. Hannu Toivonen)

    The Discovery research group carries out research in the areas of computational creativity and data mining. We are now looking for a PhD  student 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 studying computational creativity. More information on Discovery research group:
  • Scalable Probabilistic Analytics  (Prof. Petri Myllymäki)

    We are looking for a PhD candidate interested in probabilistic modelling and Bayesian inference, to work on developing computationally efficient probabilistic modelling tools. The position is funded by a Tekes project that aims to speed up the process of developing probabilistic tools for analytics demands, by combining easy-to-use probabilistic programming languages with efficient distributed inference backend. The project combines fundamental basic research with industry collaboration and opportunity to contribute to open-source software development. An ideal candidate has strong knowledge in machine learning and probabilistic modelling, with sufficient programming skills. Contact person: Academy Research Fellow Arto Klami.
  • Constraints, Satisfiability, and Optimization  (Prof. Petri Myllymäki)

    The Constraint Reasoning and Optimization group ( at University of Helsinki, led by Dr. Matti Jarvisalo, has an open position for a PhD candidate. The group has a notable track record in practical and theoretical aspects of Boolean satisfiability (SAT) and related automated reasoning formalisms. We are looking for talented and highly motivated students with background in applied and/or theoretical aspects of constraints, computational logic, and/or discrete optimization. Earlier experience in SAT, constraint programming (CP), integer programming (MIP), answer set programming (ASP), or satisfiability modulo theories (SMT) is a notable asset. Possible PhD 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.
  • Computer Vision  (Prof. Juho Kannala)
    We are a new and growing research group working broadly in the field of computer vision. We are pursuing research problems both in geometric computer vision (including topics such as visual SLAM, visual-inertial odometry, and 3D scene reconstruction) and in semantic computer vision (including topics such as object detection and recognition, and deep learning). We are looking for new PhD candidates to our group. Students with good programming skills and strong background in mathematics are especially encouraged to apply. Previous experience in computer vision is not required. The precise topics of the research will be chosen together with the students to match their personal interests. For more information about our research, please visit
  • Probabilistic Inference and Computational Biology  (Prof. Petri Myllymäki)
    The Probabilistic Inference and Computational Biology group at the University of Helsinki is lead by Academy Research Fellow Antti Honkela. We develop new probabilistic inference and machine learning methods targeting mainly on computational biology applications. We work on approximate inference, Gaussian processes and privacy-aware modelling. We are looking for new PhD candidates interested in probabilistic inference and machine learning methods development for solving  tomorrow's modelling problems. More information: