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Group, https://www.chalmers.se/en/departments/e2/research/communications-antennas-and-optical-networks/communication-systems/ , employing around 45 people, including 8 faculty and 25 PhD students. During
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and detection, coding theory, and optimization. As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or
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. The employment requires strong subject knowledge in optimization, mathematical modeling, and quantitative analysis. You are a problem solver who works well with complex issues, understands complicated written
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. Your qualifications You have graduated at Master’s level in Electrical Engineering, Computer Science, or Applied Mathematics, with a minimum of 240 credits, at least 60 of which must be in advanced
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collaboration with Lund University. The candidate is expected to have a strong mathematical background particularly in stochastic modeling, optimization, and reinforcement learning. As a PhD student, you devote
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the European Regional Development Fund. Subject description The subject includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals
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Fund. Subject description The subject includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals that are closely related
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of their biological counterparts. This project aims to overcome these limitations through a synergistic circuit–device co-design that jointly optimizes both circuit architectures and component properties, ensuring
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Computer Science Electrical and Computer Engineering Mechanical Engineering Applied Mathematics Applied Physics Statistics and Optimization A strong background in robotics, machine learning, and control is essential
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Methodological toolkit related to applied mathematics, environmental economics, game theory, or operations research Skills in data management and computational implementation of large-scale optimization models