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).
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 (email@example.com, +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.