Doctoral candidate or master's thesis student in Mechatronics

Updated: 2 months ago
Job Type: FullTime
Deadline: 30 Nov 2021

The Mechatronics research group is looking for a machine learning oriented doctoral candidate or a master’s thesis student!

The position is suitable for a doctoral candidate or for a master’s thesis student interested in machine learning applications in mechanical and rotating systems. A possibility is first to complete a master’s thesis followed by an evaluation with a possibility to proceed to doctoral studies.

The work will be conducted in ongoing research projects of the mechatronics research group, such as the CoE (Center of Excellence in electromechanical power conversion), AI-ROT (Artificial Intelligence Optimization for Rotating Machinery Governed Production Lines) or Met4wind (Metrology for enhanced reliability and efficiency of wind energy systems).

Please note that the skills and courses listed in this document are for example only, and the position can be tailored to candidates from various different backgrounds.

The research will be performed in close collaboration with industrial partners and can cover various topics, industrial applications and technologies such as:

  • Electromechanical power conversion
  • Cardboard and steel production
  • Wind energy systems
  • Applied deep learning and intelligent fault diagnosis for bearings, gears, seals and sensors
  • Surrogate models: replacing computationally expensive models with light-weight ML models
  • Virtual sensors: estimating hard-to-measure quantities in real life systems
  • Reinforcement learning: intelligent control of complex systems, optimization of roll geometry
  • Transfer learning (Sim2Real): generation of training data with simulations, test data acquisition from industry / laboratory

Skills we are looking for:

  • Programming skills
    • Python
    • Pytorch or similar
    • C/C++
    • Version control
  • Mechanical engineering studies
    • Rotating machinery
    • Mechanics of materials / vibrations of structures
  • Machine Learning / data science
    • Basic understanding of deep learning techniques such as RNNs / CNNs
  • Signal processing skills:

Recommended courses:

How to apply

Please submit your application latest on November 30, 2021 through our recruiting system by using the "Apply!" link above. If you are already working at Aalto, please apply via our internal system Workday -> Find Jobs.

Please include the following pdf documents in English:

  • Motivation letter, with specific focus on ML applications in mechanical systems
  • CV and other proof of scientific activity (publications, conference papers etc.)
  • Certified copies of the completed degrees certificates and official transcripts of records, and their translations, if the originals are not in Finnish, Swedish or English
  • Proof of proficiency in Finnish, Swedish or English if the applicant is not a native speaker of them
  • Copy of Master thesis if applicable

The applicant for the position Doctoral Candidate must have a master’s degree and must fulfill the requirements for doctoral students at the Aalto University School of Engineering. Please find more information from here:  https://into.aalto.fi/display/endoctoraleng/How+to+apply#Howtoapply-Eligibilityandadmissioncriteria

We will start reviewing candidates during the application period already. We encourage you to apply as soon as possible, as the department reserves the right to end the call and make an offer as soon as a potential candidate is found.

Further information

For additional information on the position, please contact Assistant Professor Raine Viitala, raine.viitala@aalto.fi . In case you have questions related to the recruitment process, please contact HR-coordinator Jenni Koivisto, jenni.koivisto@aalto.fi .

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