Two postdoc positions with focus on Neuromorphic sensing for condition monitoring applications
Sergio MDCB
Luleå University of Technology experiences rapid growth with world-leading expertise within several research domains. We shape the future through innovative education and groundbreaking research results and drawing on our location in the Arctic region, we create global societal benefit. Our scientific and artistic research and education are carried out in close collaboration with international, national and regional companies, public actors and leading universities. Luleå University of Technology has an annual turnover of SEK 1.8 billion. Today, we have 1,770 staff and 17,200 students.
In the coming years, multi-billion investments will be made in large projects in Northern Sweden to create a fossil-free society both nationally and globally. Luleå University of Technology is involved in several of these cutting-edge research projects and in the societal transformation that they entail. We offer a broad range of courses and study programmes to match the skills in demand. We hope that you will help us to build the sustainable companies and societies of the future.
This postdoctoral fellowship is part of a project funded by The Kempe Foundations that focuses on Neuromorphic sensors for advanced condition monitoring with wireless sensors. The project comprises a total of two postdocs (Ref no. LTU-527-2022 and LTU-578-2022) and is a collaboration between the division of Machine Elements and Embedded Intelligent Systems (EISLAB). This scholarship in Machine Learning at Machine Elements concerns research with a focus on establishing knowledge required to design effective neuromorphic condition monitoring sensors including suitable filter banks and amplifiers for these.
EISLAB at the department of Computer Science, Electrical and Space Engineering conducts research and education in the areas of cyber-physical systems (CPS), machine learning (ML) and electronic systems (ECS). The research is both of a fundamental research nature and of an applied character and is often done in close cooperation with the Swedish and international industry. We have a long tradition of working together with researchers at ME in condition monitoring related projects, where the knowledge at EISLAB in combination with knowledge of tribology and machine applications at ME gives an outstanding basis for developing new condition monitoring concepts and solutions.
The Division of Machine Elements (ME) at the Department of Engineering Sciences and Mathematics (TVM) is a research group that enthusiastically works for a more sustainable world with a diminishing climate and environmental impact. Many activities at ME include different aspects of tribology, e.g., tribology of machine components, condition monitoring, materials tribology, lubrication and lubricants and computational tribology. The research is both of a fundamental research nature and of an applied character and is often done in close cooperation with the Swedish and international industry. The branch working with condition monitoring also has a long tradition of working together with researchers at EISLAB, where the knowledge in tribology and the machine applications present at ME in combination with knowledge in electronics and machine learning found at EISLAB gives an outstanding foundation for developing high-performing condition monitoring systems of machine components and applications.
By taking part in this collaboration you will work in an international, creative resourceful environment with an extensive international contact network. EISLAB participates in national research projects and large EU projects. Collaboration with industry takes place via center formations such as ProcessIT (process automation), CDT (telecom & data center) and CISS (security). The research group is one of the leading tribology research groups in Europe and there are good opportunities for exchanges with other groups in Europe and other parts of the world.
Project description
Neuromorphic (i.e., brain-like and event-driven) processors are being developed to solve sustainability challenges in artificial intelligence (AI) and digitization, especially related to energy efficiency and resource needs. By emulating the brain, where information about changes (events) drives dynamic processes for information processing, new efficient sensor systems are made possible. Condition monitoring is expected to become an important application area and market segment. However, there is a lack of knowledge about event-based sensors for such applications.
The scholarship is intended for research that aims to develop new knowledge about neuromorphic and event-driven sensor systems for advanced condition monitoring, e.g., about filterbanks, charge amplifiers and system solutions adapted for integration with neuromorphic processors. You will work closely with other LTU researchers and participate in the supervision of doctoral students, especially in collaboration with a postdoc at the division of EISLAB at the department of Computer Science, Electrical and Space Engineering which focuses on the neuromorphic sensing principles and data analysis. Parts of the work will be carried out in Tribolab, one of Europe’s largest laboratories for tribological research, to measure and process data from real machine components and develop and evaluate filter-banks suitable for these applications.
Application
We prefer that you apply for the position via the application button below, where you attach a personal letter as well as a CV / curriculum vitae, grades and diploma. Please mark your application with the reference number below. Applications and diplomas must be written in Swedish or English.
Application deadline: April 10, 2022
Scholarships for Post docs - Luleå University of Technology (ltu.se)