Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
of Competence in Research (NCCR) “SPIN: Spin Qubits in Silicon" supported by the Swiss National Science Foundation. The NCCR SPIN is developing fundamental elements of scalable quantum computing with spins qubits
-
of Basel is the home institution of the Swiss National Center of Competence in Research (NCCR) “SPIN: Spin Qubits in Silicon” supported by the Swiss National Science Foundation. The NCCR SPIN is developing
-
" supported by the Swiss National Science Foundation. The NCCR SPIN is developing fundamental elements of scalable quantum computing with spins qubits in silicon and germanium. More details are available from
-
language processing, algorithmic learning, fault-tolerance, blockchains, consensus, cryptocurrencies, digital money, central bank digital currency, decentralized finance, financial networks, e-democracy, voting, social
-
resettlement. The position is part of an innovative project using machine learning and matching algorithms to improve the resettlement process for refugees and asylum seekers. We are developing GeoMatch , a
-
responsibilities may include: Development or analysis of novel Machine Learning algorithms for engineering design applications, such as Inverse Design, Surrogate Modeling, or generative modeling. Collaborating with
-
seismology, geothermal energy, and geobiology. Access to cutting-edge tools, algorithms, and high-quality seismic datasets. Competitive salary and benefits, including academic development and training
-
postdoctoral researcher, your responsibilities may include: Development or analysis of novel Machine Learning algorithms for engineering design applications, such as Inverse Design, Surrogate Modeling
-
programme Reference Number 5504-00 Is the Job related to staff position within a Research Infrastructure? No Offer Description Your tasks Develop advanced constitutive models for chemo-mechanical coupling in
-
-driven methods to include prior information about the underlying system Addressing process specific nonlinearities and system-theoretic properties to develop novel control and machine learning algorithms