Available positions

please see the application procedure

(1) Advanced methods for search and enumeration, Professor Petteri Kaski, Department of Information and Computer Science, Aalto University.

This project seeks to develop novel advanced methods to solve (NP-hard) search and enumeration problems on graphs and other combinatorial structures. Also of interest are selected polynomial-time problems to which the aforementioned can be reduced to with moderately exponential resources. The core of the methodology is in many cases algebraic, e.g. one relies on (multi)linear dependence or homomorphic simplification to save resources over classical algorithm designs. An ideal applicant for the position has a demonstrated strong background in at least one of the following: algorithm design (in particular, parameterised and exact algorithms), algebra (multilinear algebra, representation theory), combinatorics (graph theory, partial orders, additive combinatorics). Skills in algorithm engineering are a further merit. For more information, contact Prof. Petteri Kaski ([email protected]). A recent review article that highlights and illustrates work in the area is: http://dl.acm.org/citation.cfm?doid=2428556.2428575

(2) Big Data processing, Distributed Computing Group, Associate Professor Keijo Heljanko, Department of Computer Science and Engineering and Helsinki Institute for Information Technology HIIT, Aalto University.

The research of the group focuses on methods for distributed processing of Big Data using systems such as Hadoop and Apache Spark. Also large scale database systems for Big Data are of interest to us. Candidates with a background in Big Data processing are most welcome, good programming skills, machine learning, or formal methods for distributed systems backgrounds are considered a plus. See: http://cse.aalto.fi/en/research/groups/distributed_computing_group/

(3) Complex Systems Computation Research Group (CoSCo) led by Professor Petri Myllymäki, Department of Computer Science & HIIT, University of Helsinki.

CoSCo is a part of the The Finnish Centre of Excellence in Computational Inference Research (COIN), and we are looking for candidates with a strong background and interest in at least one of our focus areas involving topics like machine learning, probabilistic inference, information-theoretic modelling, constraint reasoning, optimization, ubiquitous computing, user modelling and big data. For more information, please visit http://www.hiit.fi/cosco/

(4) Computational biology and regulatory genomics, Professor Harri Lähdesmäki, Department of Information and Computer Science, Aalto University.

The Computational Systems Biology group at Aalto University uses computational and statistical techniques to model molecular mechanisms and their role in health and disease. In this project we aim to reveal transcriptional and epigenetic mechanisms in human cells using a variety of next generation sequencing data. Research is carried out together with Finnish and international collaborators offering the possibility to test novel computational predictions in real biological systems. We invite applications for an open postdoc position. 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 in a truly interdisciplinary setting. For more information, see http://research.ics.aalto.fi/csb/ or contact Harri Lähdesmäki ([email protected]).

(5) Crowdsensing applications for distributed cloud infrastructure, Professor Antti Ylä-Jääski, Department of Computer Science and Engineering, Aalto University.

Join us developing distributed cloud infrastructure to provide high performance and end-to-end optimized solutions for latency-sensitive and storage-sensitive as well as bandwidth-intensive and compute-intensive mobile and pervasive on-line applications. The mobile crowdsensing services are used on smart phones, tablets and increasingly through other pervasive and wearable Internet connected devices like activity tracking wristbands, smart watches, Google Glasses, cars and home appliances. The use-cases include crowdsourced video and imaging, smart traffic, efficient processing of Big Data. http://cse.aalto.fi/en/

(6) Formal Methods and Cyber-Physical Systems, Professor Stavros Tripakis, Department of Information and Computer Science, Aalto University.

The candidate will work in the Formal Methods and Cyber-Physical Systems (FM-CPS) Research Group at ICS Dept., Aalto University, headed by Prof. Stavros Tripakis. The position also includes the possibility to collaborate with researchers at (and visit) the University of California, Berkeley. For more information, email Stavros Tripakis ([email protected]).

(7) Open position for Senior / Postdoc Developer for Future Intelligent Information Retrieval, Professor Giulio Jacucci, Department of Computer Science & HIIT, University of Helsinki.

Unique position to lead the development of a future generation system for Intelligent Information Retrieval. The position has both development of a system for real wide deployment as also cutting edge research environment with academic impact. As senior / postdoc developer the candidate will be responsible of leading the development of a new generation intelligent information retrieval system that is utilising latest techniques in distributed computing, machine learning, adaptive computing, visualisation and user modelling.

Beside academic research activities the practical work includes: Programming backend, organising modular development, issuing guidelines for development.

Needed competencies and experiences: wide experience in programming in large real deployment projects, Strong skills in selected programming languages, experience of appropriate frameworks (MVC frameworks, such as Spring), Hands on experience in Web development, Experience in working with DBs - MongoDB, Postgres, etc. Duration: 5 years, salary 3 200–4 000 according to qualifications.

(8) HIIT-Wide Focus Area “Information Exploration”

The HIIT-wide focus area is a big multidisciplinary project spanning several research groups of Helsinki Institute for Information Technology HIIT at Aalto University and University of Helsinki. Several postdoc positions are now offered in the project. The postdocs will collaborate with several PI's.

Information Exploration, a central aspect of Knowledge and scientific work, can be profoundly improved through computational and information retrieval methods. Novel intelligent systems will be able to better utilize the massive explosion in raw data, documents, distributed information and links between these. Information Exploration as a focus of research develops information technology methods and pilot applications for making the data-driven fields such as modern biology, business intelligence, and others revolutionizing the way we search and access and share information. In particular improving the general problem solving method of science, in collaboration with the other fields, is the best way for our research community to contribute to solving the grand challenges of the humanity. http://www.hiit.fi/augmentedresearch

Example profiles and positions:

• Analysing ubiquitous sensor data
• Interactive Visualization
• Psychophysiology for Implicit Interaction and Brain Computer Interfaces
• Intelligent user interfaces, Information Retrieval, Recommender Systems
• Machine Learning and Data Analysis for Context based information retrieval
• Probabilistic modelling and data analysis for bioinformatics

(9) Probabilistic modelling and data analysis for bioinformatics, HIIT-wide focus area spanning several HIIT research groups; Involved Principal Investigators include Professor Samuel Kaski and Dr Antti Honkela, Helsinki Institute for Information Technology HIIT, Aalto University and University of Helsinki.

In the HIIT-wide focus area we are developing machine learning methods for molecular biology data that integrate user expertise in probabilistic models. Our team combines bioinformatics, machine learning and algorithmics researchers.

You should have a strong background in machine learning, probabilistic modelling or statistics. Previous experience in biology is not necessary, but interest in biological applications is important. More information: http://www.hiit.fi/u/ahonkela/hiit_postdoc2014.html

(10) Statistical machine learning, Professor Samuel Kaski, Helsinki Institute for Information Technology HIIT, Aalto University and University of Helsinki.

We are looking for candidates interested in doing basic research in statistical machine learning and its applications. Our core expertise is learning from complex and multiple data sources, a problem that arises in application fields ranging from proactive interfaces and data visualization to computational biology, medicine, computational neuroscience, and epigenetic studies. Keywords include probabilistic modelling, Bayesian inference, Big Data and small data. We belong to the Finnish Centre of Excellence in Computational Inference Research COIN and Biocentrum Helsinki. http://research.ics.aalto.fi/mi/

(11) Smart society initiative, coordinated by Helsinki Institute for Information Technology HIIT, Aalto University. Contact persons: Ella Bingham, research coordinator of HIIT and Samuel Kaski, director of HIIT.

The breadth of Aalto University and University of Helsinki offer tremendous so-far underused opportunities to revolutionize fields of science, services and society with computational and IT techniques, see http://www.aalto.fi/en/research/platforms/digi/. We are looking for pioneers, both research fellows and postdocs, interested in collaborating with one computer science group and an application field group. The first stage of this initiative starts from Aalto School of Science but the collaborating group can be elsewhere. Requirement is excellence in computer science; contact us for more information if needed.

(12) Finnish Centre of Excellence in Computational Inference Research (COIN), Aalto University and University of Helsinki.

COIN develops methods for transforming the data produced by the current data revolution into useful information. The key methodology for achieving this goal is statistical and computational inference based on the data. The emphasis is on large data collections and computationally demanding modelling and inference algorithms. Our mission is to push the boundary towards both more complex problems, requiring more structured data models, and towards extremely rapid inference. COIN brings in expertise on several different approaches to inference, with a unique opportunity to address the core computational challenges with combinations of machine learning, computational statistics, statistical physics, and constraint-based search and optimization. Our flagship application areas include Intelligent Information Access and Computational Molecular Biology and Medicine.

There are opportunities for both methods development and theoretical work, and interdisciplinary applications. http://research.ics.aalto.fi/coin/

(13) Helsinki Institute for Information Technology HIIT Open Call for Postdocs and Research Fellows.

HIIT offers postdoc and research fellow positions for outstanding candidates, to be affiliated with any of its research groups (http://www.hiit.fi/groups). Please indicate in your application which research group(s) you are interested in and modify your research plan to support the research areas of the corresponding professor(s) in charge. Requirement for these open positions is substantial prior experience outside the particular group.