20 distributed-algorithms-"Meta" positions at Chalmers University of Technology in Sweden
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and technical skills within a team of leading researchers in structural and algorithmic graph theory. The project focuses on exploring the tractability and intractability of graph problems in both
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to continuation as a researcher at Ericsson Research. Practical work tasks include: Developing algorithms and models for dynamic spectrum sharing using RDT data Implementing and evaluating signal processing and
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, develop theory and algorithms for their practical use, and study complexity and performance trade-offs in relevant applications. The project is led by Professor Erik Agrell (IEEE Fellow), whose
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. The current position deals with free-space optical transmission experiments. It will involve challeges with low SNR, atmospheric turbulence issues, coherent recevers and related signal processing algorithms
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The project is in the field of optimization, and in particular the project focuses on the design of approximation algorithms for multi-dimensional packing and scheduling problems. The position offers
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to the application deadline Experience from sea ice field work or polar expeditions Experience in work with oceanographic or meteorological data and models What you will do Apply, validate and improve algorithms
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). Completed courses in signal processing, radar or communication systems. Communication skills in Swedish are valuable, but not required. What you will do Develop radar signal processing and algorithms
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Do you want to contribute to groundbreaking research in the development of a theoretical framework and numerical algorithms for evolving stochastic manifolds? This is an exciting opportunity for a
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meshing and refinement algorithms that support hierarchical levels of detail. The theoretical component includes convergence and error bounds for refinement, conditions for topological validity, robustness
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on literature from mathematics, computer science, robotics, and game theory. Join a growing research group developing state-of-the-art algorithms for agentic decision making. About us The Department of