Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- KTH Royal Institute of Technology
- Lunds universitet
- Linköping University
- KTH
- SciLifeLab
- IFM, Linköping University
- IFM/Linköping University
- Karolinska Institutet (KI)
- Linköpings universitet
- Lulea University of Technology
- Luleå University of Technology
- Mälardalen University
- Nature Careers
- SLU
- Sveriges Lantbruksuniversitet
- Umeå universitet
- University of Lund
- Uppsala universitet
- 9 more »
- « less
-
Field
-
diagnosis of gas turbines. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components
-
. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components. The aim is that fault diagnosis
-
broad spectrum of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes
-
, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
-
your application: A doctoral degree in automatic control, electrical engineering, computational materials science or related. Research experience in battery tests, machine learning, data-driven
-
year. You should have knowledge and experience in bridging quantum and classical machine learning, and be fluent in English, both written and spoken. Assesment criteria Qualifications that are considered
-
established in the areas of electronic and electromagnetic simulation and design, machine learning and artificial intelligence in electrical engineering, electrical low-frequency and high-frequency measurement
-
conduct research on the theoretical foundations of mathematical optimization, as well as its applications to emerging challenges in machine learning and engineering. You will write and submit research
-
tasks that require coordinated base-arm-hand behaviors in dynamic environments. We seek candidates with a strong background in robotics and machine learning, and demonstrated experience in at least two of
-
theory, and learning theory to design efficient and robust decentralized AI systems. As postdoc, you will principally carry out research. A certain amount of teaching may be part of your duties, up to a