Tampere University of Technology (TUT) is an active scientific community of 2,000 employees and more than 10,000 students. The University operates in the form of a foundation and has a long-standing tradition of collaboration with other research institutions and business life. Many of the fields of research and study represented at the University play a key role in addressing global challenges. Internationality is an inherent part of all the University's activities. Welcome to join us at TUT!

Doctoral student (Advanced Data Analytics of Machine Systems)

Department of Intelligent Hydraulics and Automation (IHA) is one of the leading research units in the world of fluid power automation. Research is focused on intelligent mobile machines. IHA’s ambition is to develop new innovative solutions using fluid power and automation technologies, which minimizes the environmental impact in all aspects and improves energy efficiency, productivity and usability of the systems. To fulfill the strategy the research work at IHA follows these three principles: interdisciplinary research, the bridging of theory and practice and cooperation with industry.

Novel Predictive Analytics Technologies for Future Maintenance Business (OPENS) is a new Tekes project funded by Tekes and industrial companies. It is a parallel research project of TUT/Department of Intelligent Hydraulics and Åbo Akademi/Department of Information Technologies (IT)/Embedded Systems Laboratory (ESlab). The project belongs to Industrial Internet program of Tekes (https://www.tekes.fi/en/programmes-and-services/tekes-programmes/industrial-internet--business-revolution/). The research project will create added value from Big Data and develop new intelligent and efficient analysis methods enabling new digital business solutions and services. The objective is to develop methods which are able to refine information from the multivariate disparate data and to predict the future behaviour of systems on the basis of this information. Doing this way, we can move from monitoring and evaluating the present state to predict, plan and assess future what-if scenarios and examining complex questions. In the method development, attention is also paid to the connecting of the processes of companies and expert human knowledge to data analytics which will be an essential position in the development of the future Industrial Internet (IoT). The developed methods will be tested and verified using the data collected from the machine systems of industrial partners and the test systems of the universities.
Job description: In the project described above, the fundamental task of the doctoral student is to study and develop methods in the field of knowledge extraction and predictive modelling for predictive analytics using massive data stores (Big Data) of sensor, usage and also maintenance data of machine systems (e.g. elevator systems).

In this project, frequent meetings with research partner Åbo Akademi and industrial partners will be held. Includes a few days / weeks of working in Turku per year. The validation of the developed methods involves experiments both in universities and companies.

The work will be supervised by Professor Kalevi Huhtala and Research Fellow Tomi Krogerus. The position will be located at the Department of Intelligent Hydraulics and Automation (TUT).
Requirements: The candidate should hold MSc degree in a suitable field (Data Science, Signal Processing, Information Technology etc.).

A theoretically oriented, problem-solving mind with experience of data analytics/ machine learning/ data mining definitely makes life easier with this job. Moreover, a good command in programming with Matlab, R etc. is beneficial. Good team working skills are appreciated.

Finally, the doctoral student usually has assisting teaching duties amounting approximately to 5% of the annual working hours.
Salary: The salary will be based on both the job demands and the employee's personal performance in accordance with the University Salary System. According to the criteria applied to teaching and research staff, the position of a doctoral student is placed on the job demands levels 1-4. In addition, employees receive performance based salary.
Trial period: Trial period of four (4) months applies.
Other: The position will start November 1st, 2016, or as mutually agreed upon by both parties. The position will be filled for fixed term until 31.8.2019.
For more information, please contact: Research Fellow Tomi Krogerus (tomi.krogerus@tut.fi, +358-50-3009077).
How to apply: Applications must be submitted through the University's online application form. The closing date for applications is October 5, 2016. Applications should include:
- Curriculum vitae (CV)
- Transcript of study records

Please include attachments as PDFs.
Additional information on attachments to applications.

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