Sort by
Refine Your Search
-
Listed
-
Employer
- Linköping University
- Lulea University of Technology
- SciLifeLab
- Chalmers University of Technology
- Umeå University
- Uppsala universitet
- Luleå University of Technology
- University of Borås
- KTH Royal Institute of Technology
- Karolinska Institutet
- Karolinska Institutet, doctoral positions
- Linnaeus University
- Mälardalen University
- Nature Careers
- University of Lund
- 5 more »
- « less
-
Field
-
a quantum computer based on superconducting circuits. You will be part of the Quantum Computing group in the Quantum Technology Laboratory (QTL) division of the Microtechnology and Nanoscience (MC2
-
important connections between material structure and conductivity by using advanced data-mining strategies and machin-learning. The main duties of doctoral students are to devote themselves to their research
-
, Machine Elements, Economics, and Law will commence with a consortium comprising LTU, LKAB, and Vattenfall. We are seeking three highly motivated PhD candidates to contribute to the interdisciplinary
-
12 Feb 2025 Job Information Organisation/Company University of Borås Research Field Economics » Industrial economics Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions
-
, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software
-
, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software
-
, Internet of Things, Systems-of-Systems automation, Machine Learning, Deep Learning, Data Science, Electronic systems design, and sensor systems. Cyber-Physical Systems (CPS) focuses on integrated software
-
and computer science and be fluent in oral and written English. Specific depth in mathematics, computer security or encryption is valuable but not a requirement. It is an advantage if you have previous
-
interaction combined with extensive field measurements. A digital twin of the detector will be created to train a machine learning model for predicting dynamic wheel loads. The overarching aim is to enhance
-
essentially corresponding knowledge in another way. Experience with Computational Fluid Dynamics (CFD) is advantageous, as is knowledge of quantum chemical calculations (DFT). An interest in machine learning