To support our advancements in applied industrial artificial intelligence (AI) at the University of Southern Denmark (SDU), the Section of Applied AI and Data Science (AID) at the Mærsk McKinney Møller Inst. invites candidates to apply for a 2-year post-doctoral position, to help us bring AI and machine learning into industrial applications related to the green energy.
Research and organizational environment
At the University of Southern Denmark (SDU), the candidates will join the research group of Applied AI & Data Science (AID) at the Maersk Mc-Kinney Moller Institute, at the Faculty of Engineering. Jointly with Siemens Gamesa Renewable Energy (SGRE), these research environments provide the foundations for accelerating AI in green energy representing expertise in artificial intelligence, statistical machine learning, and data science by developing methods for data-driven solutions within off-shore wind farms, wind turbines and fusion reactors.
Qualifications
We invite motivated candidates with interest in artificial intelligence and machine learning to apply. We will specifically look for candidates with documented track-record in conducting relevant technical research in the area of condition monitoring and fault detection of industrial processes. A successful candidate will have expertise in time series analysis, pattern recognition and signal processing. The candidate must hold a Ph.D. Degree in Electrical Engineering, Computer Science, Mathematics, or physics. This will enable the successful candidate to contribute to the development of a strong AI research environment at both SDU and SGRE.
The successful applicant will join a dynamic research team and will be introduced and included in other research projects. The successful applicant will be also involved in our new collaboration with EuroFusion to help design the divertor of world’s largest stellarator Wendelstein 7-X. A candidate with expertise in Physics-informed AI and quantum machine learning is preferred.
Responsibilities
Your primary responsibility is to utilize and leverage the broad technical research within AI and machine learning to support the long-term vision of AID being a world-class center in the field of clinical and industrial artificial intelligence. This follows the research strategy, which functions as backbone in one of the first centers of its kind dedicated to working on AI across a large variety of clinical and industrial areas.
Your responsibilities will be to:
- Develop, implement and execute industrial AI-focused projects in close collaborations with SGRE and Institute for Plasma Physics (IPP) at Max-Plank Inst.
- Explore and utilize the possibilities for addressing AI and machine learning in industrial setting – especially within time-series analysis, physics-informed neural networks (PINN), and quantum machine learning and AI.
- Give technical input and support for ongoing projects and establish new collaborations between researchers from SDU and SGRE.
- Contribute to teaching activities at SDU, and outreach activities targeted younger research candidates.
- Contribute to fund raising efforts that take place at AID.
For further information about the positions, please contact
- Project leader, Associate Prof. Jurgen Herp herp@mmmi.sdu.dk
- Head of Applied AI and Data Science unit (AID), Prof. Esmaeil S. Nadimi esi@mmmi.sdu.dk
Salary and terms of employment
The terms of employment are stated in the Agreement between the Ministry of Finance and the Danish Confederation of Professional Associations (AC).
The university wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
The assessment process
Read about the Assessment and selection process. Shortlisting may be used.
Application
The faculty expects applicants to read How to apply before applying.
The application must contain (only as pdf):
- A letter stating the interest, motivation, and qualifications for the project (max. 2 pages).
- Research plan (max. 2 pages)
- Detailed CV
- A complete list of publications
- Certified copy of diplomas and Ph.D. degrees in the relevant fields
- 2 most relevant publications in which the applicant wishes to rely on (preferably the applicant being the first author)
- We encourage the candidates to provide the contact information of a reference academic
Attached files must be in Adobe PDF. Incomplete applications, and applications received after the deadline will neither be considered nor evaluated. Suitable candidates will be invited for a job interview after the application deadline.
The deadline for application is Sep 1st, 2022. Job interviews are expected to be held during September 2022.
Living and working in Denmark
There are several services available for foreign applicants. International Staff Mobility at SDU provides a variety of services for new employees, guests and people who consider applying for a job at the University of Southern Denmark. Please visit this website for more information. International Community Odense at Municipality of Odense will also offer help for international employees and their families coming to Odense, helping them settle, and introducing them to social networks and activities around the city. Please visit this website for more information.
FACTS
The Maersk Mc-Kinney Moller Institute
The Maersk McKinney Moller Institute (MMMI) is part of the Faculty of Engineering at the University of Southern Denmark. MMMI is an internationally recognized research department, which has maintained a leading position in robotics for more than two decades. The team of Applied AI and Data Science is the main driver of activities within artificial intelligence and machine learning at the university of Southern Denmark. The team has close collaboration with various hospitals in Denmark, and runs projects within AI in gastroenterology, neurology, urology, cardiology and endocrinology.
Read more about AID and the Maersk Mc-Kinney Moller Institute here.
Send application
Deadline 2022-Sept-01
You can apply for the job at Faculty of Engineering by completing the application form