Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto has six schools with nearly 11 000 students and a staff of more than 4000, of which 400 are professors. Our main campus is located in Espoo, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness in the future as well. This is why we warmly encourage qualified candidates from all backgrounds to join our community.
The Department of Computer Science at the Aalto University School of Science is presently looking for a
Postdoctoral Researcher in Data Analysis and Machine Learning
The position is a part of the Aalto career system and the selected person will be appointed for a fixed-term contract with an option for renewal, if the project is extended. The position is available from now until the end of the project on October 29, 2021. The work is based in Espoo, Finland.
The Postdoctoral Researcher will be working in an international research project AutoDC, which is developing the technologies and the concept for a fully autonomous data center. The project as a whole will e.g. address the autonomous data center business impact, hardware and system design, measurement system, data collection and data engine, machine learning, prescriptive and predictive methods, management systems as well as operation and control systems. The work of the Postdoctoral Researcher will go towards reaching the overall outcome of the project, which includes the proof of concepts for the different parts of the autonomous data center as well as demonstrations of the concept in a real large-scale data center.
The work of the Postdoctoral Researcher will focus on exploratory data analysis, machine learning and predictive analytics, e.g. machine learning methods and tools for various prediction problems in the context of autonomous data centers, and the aim will be to create predictive maintenance models. The specific technologies are multivariate, autoregressive time-series prediction models and regime-switching probabilistic models for non-stationary environments. The work will need to integrate to other model-based approaches developed by other partners in the research project.
In addition to research work, person hired may be expected to participate in the supervision of students and teaching following the standard practices at the department.
The candidate should have a Ph.D. and an advanced level of understanding in the field of data analysis and machine learning. The candidate will need a good command of both written and spoken English. The candidate is expected to publish on his/her work. Team player qualities and interest in collaborating with international partners will be seen as an asset.
Compensation, working hours and place of work
The salary for the position is between 3 660 and 3 840 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 Aalto University is 1 612 hours. The position is located at the Aalto University Otaniemi campus.
Application material and procedure
Short-listed candidates may be invited to an interview. The candidates must have completed their PhD degree before the start of the contract period. Should there be a lack of eligible outstanding applicants, the application period may be extended. While all applicants who have submitted an application by the deadline will be appropriately considered, Aalto University reserves the right to consider also other candidates for the announced position.
Apply to the position via the link on Aalto University’s website:
on 15th October 2020 at 23:59 Finnish time (UTC +2) at the latest.
The applications will be handled already during the application period.
Dr Jaakko Hollmén, e-mail "firstname.lastname@example.org
" (research related information)
HR Assistant, Sanni Kirmanen, e-mail "email@example.com
" (application process, practical arrangements)