Calls

Postdoctoral Researcher and Research Fellow Positions in ICT (Helsinki, Finland)2018-11-08T10:51:18+00:00

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

Aalto University and the University of Helsinki are looking for Postdoctoral Researchers and Research Fellows in the following areas of ICT, including:

  • artificial intelligence and machine learning
  • data science
  • privacy and security
  • computational health
  • human-computer interaction
  • natural language processing

We welcome applications linking two or more of these areas together, and encourage female applicants to apply!

The deadline for applications is November 29th, 2018. By applying to this call, organized by Helsinki Institute for Information Technology HIIT, you apply with one application to both Aalto University and the University of Helsinki. The employing university will be determined according to the location of the supervising professor. Further information can be found below.

Aalto University and the University of Helsinki are the two leading universities in Finland in computer science and information technology, and Helsinki Institute for Information Technology HIIT is their joint research institute for basic and applied research in information technology. HIIT’s research is organized in the form of joint research centers and research programs. There are multiple research groups participating in each of them. The researchers to be recruited will be placed in one of the participating groups, or in some cases a shared position may also be possible. In addition, positions are available in the specific projects listed below.

Research centers and programs

Finnish Center for Artificial Intelligence (FCAI). FCAI brings together the world-class expertise of Aalto University and the University of Helsinki in AI research, strengthened further with an extensive set of companies and public sector partners, creating an attractive, world-class ICT hub in Helsinki metropolitan area. FCAI research agenda builds on our world-class expertise in machine learning, and is spearheaded by 5 research programs with multiple research groups involved in each. FCAI is currently hiring postdoctoral researchers in the following FCAI research programs. For more information see https://fcai.fi/research/):

  1. Agile probabilistic AI: Probabilistic programming; Robust and automated Bayesian machine learning.
    Several professors contribute. Contact person: Aki Vehtari
  2. Simulator-based inference: Approximate Bayesian Computation ABC; likelihood-free inference; Generative adversarial networks (GAN); applications in many fields including medicine, materials design, visualization, business, among others.
    Several professors contribute. Contact person: Jukka Corander
  3. Next generation data-efficient deep learning; including deep reinforcement learning.
    Several professors contribute. Contact person: Harri Valpola
  4. Privacy-preserving and secure AI: Privacy-preserving machine learning; differential privacy; adversarial machine learning.
    Several professors contribute. Contact persons: N. Asokan, Antti Honkela
  5. Interactive AI: Interactive machine learning; probabilistic inference of cognitive models from data; probabilistic programming for behavioral sciences.
    Several professors contribute. Contact person: Antti Oulasvirta

Director: Professor Samuel Kaski

6. Helsinki Centre for Data Science (HiDATA). Data science, i.e., extraction of knowledge and insights from data, is important across many fields of science. HiDATA, Helsinki Centre for Data Science, aims to create a world-class research and research-based education hub of data science in Helsinki, as a joint effort between the University of Helsinki and Aalto University. HiDATA builds on the existing, strong research in various areas of data science, and aims to provide novel synergies across disciplines. HiDATA is funded in 2017-2021 as part of the profiling measures of the Academy of Finland, the University of Helsinki and Aalto University, and will get to full speed during 2018.

Director: Professor Sasu Tarkoma

7. HAIC Research Program (HAIC-R). HAIC (Helsinki-Aalto Center for Information Security) is a strategic initiative set up by Aalto University and the University of Helsinki in June 2016 to ensure excellence in information security research and education. During the last few years, Aalto University and the University of Helsinki have built up strong research groups and education programs in information security and privacy. HIIT hosts the research arm of HAIC as a research program. The long-term mission of the HAIC Research Unit 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.

Director: Professor Valtteri Niemi

8. Foundations of Computational Health (FCHealth). The FCHealth programme aims to solve hard computational challenges faced upon the emerging digitalization and wide adoption of data-driven approaches in healthcare. We combine 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).

Director: Professor Veli Mäkinen

Specific projects

9. Adaptive Techniques for Approximate Counting (ATAC), Associate Professor Mikko Koivisto, Department of Computer Science, University of Helsinki

My group works on algorithms for hard counting problems, with applications to machine learning. We are particularly interested in estimation methods that have provable accuracy guarantees but that need not run in polynomial time in the worst case. We are looking for a postdoc with excellent analytic skills, good programming skills, and publications at top venues of AI, ML, or algorithms. More information on my research page.

10. Speech Recognition and Language Modeling, Associate Professor Mikko Kurimo, Department of Signal Processing and Acoustics, Aalto University

The speech recognition group focuses on machine learning in automatic speech recognition and language modeling. We are now looking for a 1-3 year postdoc to start asap. A more senior researcher position can also be considered. The positions require a relevant doctoral degree in CS or EE and skills for doing excellent research in an (English-speaking) group. Requests for further information should be sent by email to prof. Mikko Kurimo.

11. Non-parametric probabilistic machine learning, Associate Professor Harri Lähdesmäki, Department of Computer Science, Aalto University

We are looking for a postdoc to develop non-parametric and deep machine learning methods for time-series and structured data, including e.g. data-driven non-parametric ordinary and stochastic differential equations and non-stationary/deep Gaussian processes with sparse approximations and inference methods. Applicants are expected to have strong background in probabilistic modeling, machine learning, programming, and have previous experience with (or desire to learn) auto-differentiation/Stan/TensorFlow. For more information and relevant recent publications, see (http://research.cs.aalto.fi/csb/publications) or contact Harri Lähdesmäki (harri.lahdesmaki@aalto.fi).

12. Bioinformatics and computational biology, Associate Professor Harri Lähdesmäki, Department of Computer Science, Aalto University

We are looking for a postdoc to develop advanced bioinformatics and probabilistic machine learning methods for high-throughput sequencing data with applications to e.g. single-cell cancer immunotherapy and personalised medicine. Work is carried out in collaboration with molecular biology and biomedical research groups in Finland and abroad. Applicants are expected to have strong background in bioinformatics, probabilistic machine learning/modeling, high-throughput data analysis, and programming. For more information and relevant recent publications, see (http://research.cs.aalto.fi/csb/publications) or contact Harri Lähdesmäki (harri.lahdesmaki@aalto.fi).

13. Category theory for multi-model databases, Associate Professor Jiaheng Lu, Department of Computer Science, University of Helsinki

I am looking for a postdoc or research fellow to join the Unified database management (UDBMS) group to work on category theory for multi-model databases. The research focus of this job is to develop new principles for a novel unified database management system based on category theory. The candidate should be in mathematics or computer science background. More information: http://udbms.cs.helsinki.fi/

14. Natural language generation, Professor Hannu Toivonen and Dr. Mark Granroth-Wilding, Department of Computer Science, University of Helsinki

We are looking for a postdoc to join the Discovery Research Group and its two European projects, NewsEye and Embeddia. Both projects revolve around analysis of news stories and generation of new text. NewsEye has a focus on old newspaper archives while Embeddia works with current news. We are now looking for candidates primarily for natural language generation (NLG). NewsEye will involve collaboration with Digital Humanities researchers. The background of an ideal candidate contains both computer science and natural language processing/language technology; previous experience with NLG is not required. Competence in a variety of machine learning techniques is desirable. We offer opportunities for both international and cross-disciplinary collaboration.

15. Human-guided data analysis, Associate Professor Kai Puolamäki, Department of Computer Science and Institute for Atmospheric and Earth System Research (INAR), University of Helsinki

The exploratory data analysis group is looking for several postdocs for 1-2 years, to start as soon as possible. The topics of interest include the use of randomization and simulation methods to model user’s knowledge, interpretable models, and human-computer interfaces in data analysis; the exact topic can be tailored taking the expertise and interests of the applicant into account. Part of the work may be done in collaboration with Institute for Atmospheric and Earth System Research (INAR). A more senior researcher position can also be considered. The positions require a relevant doctoral degree, e.g., in computer science, statistics, mathematics, or physics, and ability to work in an environment with English as a working language. Please contact Prof. Kai Puolamäki at kai.puolamaki@helsinki.fi for further information.

16. Estimation and machine learning algorithms for navigation, Associate Professor Laura Ruotsalainen, Department of Computer Science, University of Helsinki

Spatiotemporal data analysis research group is looking for a postdoc to develop estimation and machine learning algorithms for pedestrian navigation and automated traffic. Development of sophisticated algorithms is needed to secure the computation of accurate and reliable navigation solution in challenging environments such as urban canyons and indoors, and to detect and mitigate the effects of intentional interference of satellite positioning. Applicants are expected to have strong background in machine learning, statistics and programming. The position requires a relevant doctoral degree, e.g., in computer science, statistics or mathematics, and ability to work in an environment with English as a working language. Please contact Laura Ruotsalainen at laura.ruotsalainen@helsinki.fi for further information.

17. AI for ultrasonic cleaning, Assistant Professor Arto Klami, Department of Computer Science, University of Helsinki

We are looking for a postdoc or research fellow to develop machine learning and artificial intelligence technologies for ultrasonic industrial cleaning. The position is shared between University of Helsinki and Altum Technologies, and offers a unique opportunity to combine fundamental research in artificial intelligence for ultrasonics with hands-on work in cleantech business with extreme growth. Altum Technologies won the main pitching contest of SLUSH 2017. An ideal candidate combines strong research background in machine learning or related field with proven skills and enthusiasm in delivering practical AI systems, and is willing to simultaneously work on open research problems while building production-quality systems. Expertise in probabilistic modelling, deep neural networks, inverse problems, and signal processing are strong advantages. We are also willing to consider candidates with PhD in computational physics willing to transition to artificial intelligence, but expect some background in the field. For more information, contact Arto Klami (arto.klami@cs.helsinki.fi).

18. Computational HCI, Associate Professor Antti Oulasvirta, Department of Communications and Networking, Aalto University

The User Interfaces group at Aalto University is looking for a postdoctoral scholar for exciting research topics at the intersection of computational sciences and human-computer interaction. The group is funded by a European Research Council (ERC) grant and consists of five postdocs, three PhD students, and two assistants. The research topics include fundamental aspects of computational design and interaction: model acquisition from data, simulation and cognitive models, optimization and machine learning methods, interactive support for designers, as well as demonstrators in key application of HCI. We invite applications from outstanding individuals with suitable background for example in Computer Science, Data Sciences, Human-Computer Interaction, Computational Statistics, Machine Learning, Information Visualization, Neurosciences, or Cognitive Science.

For more information and relevant recent publications, see Homepage of PI Antti Oulasvirta with example papers and group homepage.

19. Multi-omics machine learning for personalized medicine, Professor Tero Aittokallio, Institute for Molecular Medicine Finland

The FIMM Computational Systems Medicine research group led by Tero Aittokallio focuses on developing and applying integrated computational-experimental approaches to tackle biomedical questions. The group is now seeking a motivated postdoctoral researcher, with an interest in applying machine learning and other computational approaches for analysing, modeling and integration of large-scale drug testing and multi-omics molecular profiling datasets. As an example of a multidisciplinary research project, we are collaborating in grand challenge research in individualized systems medicine at FIMM, where our objective is to integrate genome-wide genomic profiles of cancer patients with their drug response profiles, with the aim of finding individualized treatment options based on multi-omics panels of response-predictive biomarkers.

20. Probabilistic Machine Learning, Professor Samuel Kaski, Department of Computer Science, Aalto University

I am looking for a postdoc or research fellow to join the Probabilistic Machine Learning group, to work on new probabilistic modelling methods and inference techniques. The work can include both theoretical and applied component. The group has excellent opportunities for collaboration with top-notch partners in multiple applications, for instance in personalized medicine, human-in-the-loop and interpretable machine learning, privacy-preserving machine learning, neuroscience, likelihood-free inference and Bayesian deep learning. More information: http://research.cs.aalto.fi/pml/

21. Machine learning for simulator-based inference, Aalto University / University of Helsinki

We have recently released the leading software for doing inference about simulator-based statistical models using a combination of Bayesian optimization and sampling techniques (ELFI, Lintusaari et al. JMLR 2018). We are looking for a post doc or research fellow to spearhead the further development of inference tools in ELFI and its applications in science, technology and medicine. The work can involve both theoretical and applied elements – this is a part of a bigger project that comes with a number of opportunities. We are also open to particular research topic proposals within this area from the candidates.

Several professors contribute; see also projects 22 and 23. Key professors: Jukka Corander (University of Helsinki), Samuel Kaski (Aalto University), Jaakko Lehtinen (Aalto University).

22. Intelligent user interfaces and techniques for interacting with AI, Aalto University / University of Helsinki

Appropriate methods for interacting with AI is an outstanding research problem cross-cutting AI, ML, and HCI. We have recently contributed to the study of principles of adapting and generating user interfaces automatically [1]. We are looking for a postdoc or research fellow to study interaction techniques and interface technology, with applications in science, technology and medicine. We are open to research topic proposals within this area from the candidates. The work can involve both theoretical (modeling, inference algorithms) and applied elements. The work is part of a bigger project with excellent opportunities to develop and apply modern probabilistic modelling and inference techniques.

Several professors contribute; see also projects 21 and 23. Key professors: Antti Oulasvirta (Aalto University), Kai Puolamäki (University of Helsinki).

[1] Computational Interaction, Oxford University Press, 2018

23. Interactive workflow support for probabilistic programming based modeling, Aalto University / University of Helsinki

Probabilistic programming enables fast model building and refinement of models that match the data and capture the domain knowledge of the user. We are looking for a postdoc or research fellow to develop interactive tools to support probabilistic programming and model building workflow including visual and interactive model and inference checking techniques and machine assisted suggestions for model refinement. The work is in the front-line of computational statistics involving theory, methods, computation, and applied elements. The work will be done in collaboration with probabilistic programming framework developers (e.g. Stan development team). Interaction and user modeling parts are supported by other parts of a bigger project with excellent collaboration.

Several professors contribute; see also projects 21 and 22. Key professors: Arto Klami (University of Helsinki), Aki Vehtari (Aalto University

24. Machine Learning for Human Brain-Signal Analysis, Dr. Tuukka Ruotsalo, Department of Computer Science, University of Helsinki

We are looking for a postdoc to join a team working on predicting cognitive states of humans from brain signals. The position requires a relevant doctoral degree in computer science, familiarity with machine learning methods, and good programming skills in Python. Experience in analyzing EEG data and experience in deep learning are advantages, but are not required. Please contact Dr. Tuukka Ruotsalo at tuukka.ruotsalo@helsinki.fi for further information.

How to apply

The applications are to be submitted through the eRecruitment system. Choose in the application form one or more of the research centers, programs and/or projects described above and explain in the motivation letter how you could contribute in the selected research area(s).

Required attachments:

  • Motivation letter including a tentative plan for the research work (1-5 pages)
  • CV
  • List of publications
  • A transcript of the doctoral studies and the degree certificate of the PhD degree

All material should be submitted in English. The application materials will not be returned. Short-listed candidates may be invited for an interview either at the Otaniemi or Kumpula campus or for an interview conducted via Skype.

Qualifications

The candidate should have a PhD and is expected to have an excellent track record in scientific research in one or several fields relevant to the position. Good command of English is a necessary prerequisite. In the review process, particular emphasis is put on the quality of the candidate’s previous research and international experience, together with the substance, innovativeness, and feasibility of the research plan, and its relevance to the research group or groups in question. Efficient and successful completion of studies is considered an additional merit.

Compensation, working hours and place of work

The salary for a postdoctoral researcher starts typically from 3 450 EUR per month depending on experience and qualifications. In addition to the salary, the contract includes occupational health benefits, and Finland has a comprehensive social security system. The annual total workload of teaching staff at the recruiting universities is 1 624 hours.

The position is located at Aalto University’s Otaniemi campus or the University of Helsinki’s Kumpula campus. The positions belong to the university career system and the selected persons will be appointed for fixed-term positions, for postdoctoral researchers typically for two years with an option for renewal. For exceptional candidates, a longer term Research Fellow position can be considered. The length of the contract and starting and ending dates are negotiable. In addition to research work, the persons hired are expected to participate in the supervision of students and teaching following the standard practices of the hiring department.

About Helsinki

The Helsinki Metropolitan area forms a world-class information technology hub, attracting leading scientists and researchers in various fields of ICT and related disciplines. Moreover, as the birth place of Linux, and the home base of Nokia/Alcatel-Lucent/Bell Labs, F-Secure, Rovio, Supercell, Slush (the biggest annual startup event in Europe) and numerous other technologies and innovations, Helsinki is fast becoming one of the leading technology startup hubs in Europe. As a living and working environment, Finland consistently ranks high in quality of life, and Helsinki, the capital of Finland, is regularly ranked as one of the most livable cities in the world.

About the host institutions

Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to high-quality research with significant impact on the international scientific community, industry and business, as well as the society at large. Aalto is an international community: more than 30% of our academic personnel are non-Finns. Aalto University has six schools with nearly 20 000 students; it is in world’s top-10 of young universities (QS Top 50 under 50).
For more information, see https://www.aalto.fi/en/.

The University of Helsinki, established in 1640, is the most versatile university in Finland. The University of Helsinki is an international academic community of 40,000 students and staff members. The university lays special emphasis on the quality of education and research, and it is a member of the League of the European Research Universities (LERU). For more information, see https://www.helsinki.fi.

Helsinki Institute for Information Technology HIIT is a joint research institute of Aalto University and University of Helsinki for basic and applied research on information technology. For more information, see https://www.hiit.fi/.

Further information

  • Research related questions: The leader of the research center/program/project specified above
  • Application process and practicalities: Akseli Kohtamäki (firstname.lastname@aalto.fi)

Apply