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dynamos and connect them to exoplanet discovery and space‑weather environments. You will work in Aalto’s High‑Performance Computing Lab within the PEAS (Population of Exoplanets around Active Suns
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‑weather environments. You will work in Aalto’s High‑Performance Computing Lab within the PEAS (Population of Exoplanets around Active Suns) consortium alongside leading teams in stellar astrophysics
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groups. This may draw, among other areas, on research in computational history and work with large-scale textual, bibliographic, and cultural heritage data using AI, high-performance computing, and
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, FAIR principles, and linked data. Data-intensive research computing: reproducible workflows, containers, high-performance computing, Slurm environments, and the appropriate use of GPU resources
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with transistor-level circuit design and simulation What We Offer We provide GPU computing for machine learning on Aalto's Triton high-performance computing cluster, alongside industry-standard
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-performance computing infrastructure, and evaluation using objective metrics and subjective listening tests. Your network and team You will be supervised by Assistant Professor Lauri Juvela , who leads the
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learning experiments on high-performance computing infrastructure, and evaluation using objective metrics and subjective listening tests. Your network and team You will be supervised by Assistant
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-level circuit design and simulation What We Offer We provide GPU computing for machine learning on Aalto's Triton high-performance computing cluster, alongside industry-standard circuit simulation tools
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in heat transfer, mathematical methods in engineering physics, and a demonstrated interest in numerical methods, and high-performance computing. Applicants should hold a master’s degree with excellent
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: Developing signal models, algorithms, and performance analyses for backscatter-assisted non-line-of-sight positioning Applying detection and estimation theory to questions such as detectability