28 genetic-algorithm-computer "Integreat Norwegian Centre for Knowledge driven Machine Learning" positions at Chalmers University of Technology in Sweden
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Familiarity with optimization algorithms and design of experiments methodologies Experience with high-performance computing environments Track record of publications in peer-reviewed journals Previous
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Recognised Researcher (R2) Country Sweden Application Deadline 29 Sep 2025 - 22:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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operation Quantum algorithm implementation and benchmarking About you You have a relevant Masters deegree corresponding to at least 240 higher education credits (Physics, Nanotechnology, Engineering, Computer
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We invite applications for several postdoctoral research positions in experimental quantum computing with superconducting circuits. You will work in the stimulating research environment
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Application Deadline 28 Sep 2025 - 22:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 304--1
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). Meritorious: It is also an advantage if you have experience with: Machine learning. Coupling algorithms of fluid-structure interaction solvers. Computational aeroacoustics. Swedish is not required
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of computational fluid dynamics (CFD). Knowledge of finite element method (FEM). Meritorious: It is also an advantage if you have experience with: Machine learning. Coupling algorithms of fluid-structure interaction
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, the work might involve implementing new algorithms in the SCT tool Supremica, which is developed by the Automation group. Main responsibilities Conduct research in collaboration with senior researchers and
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theoretical research, algorithm design, and the development of software tools that demonstrate the applicability of the new methods. Research environment The positions are hosted by the Department
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modular, scalable, and transparent control algorithms suitable for real-time implementation across different vehicle platforms. - Contribute to theoretical developments in stochastic model predictive