Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Curtin University
- NTNU - Norwegian University of Science and Technology
- University of Groningen
- University of Southern Denmark
- Aalborg University
- Technical University of Munich
- University of Twente
- Monash University
- Nature Careers
- University of Copenhagen
- ;
- ; Brunel University London
- Aarhus University
- Blekinge Institute of Technology
- Copenhagen Business School , CBS
- Ghent University
- Queensland University of Technology
- SciLifeLab
- Technical University of Denmark
- Umeå University
- University of Adelaide
- University of Bern
- University of Bremen •
- University of Oslo
- University of Southern Queensland
- 15 more »
- « less
-
Field
-
novel opportunity to automate and improve the frailty assessment process, aiming for greater consistency and predictive accuracy. Aims i) Develop a deep learning algorithm to autonomously detect and
-
learning arenas. Symbiosis aims to reinforce the foundations for responsible, trustworthy, and sustainable use of AI in our educational institutions by developing ethical and sustainable principles to guide
-
and empirically oriented, focusing on how political ideas, actors, and conflicts are shaped and mediated through digital platforms. Central themes may include, for example, algorithmic influence
-
interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life
-
, letters of recommendation, etc). What happens next? The assessment of potential candidates is made primarily based on academic results from bachelor degree and master degree studies. Short-listed applicants
-
better and faster decisions when assessing funding applications, ensuring the efficient and unbiased elimination of poor applications? This question can be addressed through training algorithms on past
-
electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power
-
and reproducible research, e.g., in the development of codes and algorithms. We will focus on devising computational solutions that can immediately be of use in other applications contexts as well
-
as well as in industrial applications. The endeavour to develop, analyse and optimise models and algorithms for deterministic parameter identification problems, which are formulated as high-dimensional
-
algorithm. Design methods: Develop novel control methods for power electronic converters feeding electric machine Simulation: Learn advanced simulation tools such as Ansys to simulate and analyze the effect