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deadline Experience with urban acoustic monitoring or transportation noise assessment Programming skills in Python Knowledge of machine learning techniques applied to acoustic or environmental data
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-Geometric Foundations of Deep Learning or Computer Vision KTH Royal Institute of Technology, School of Engineering Sciences Job description The Department of Mathematics at KTH welcomes applications for a
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and free-energy calculations in explicit solvent. The postdoctoral researcher will employ machine-learning-accelerated methods throughout the workflow, contribute to the development of new computational
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geometries. However, AM-generated surfaces exhibit significant and highly irregular roughness, a key factor that strongly modifies turbulence, pressure drop, and heat transfer. Unlike conventional machined
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, development of chemical process solutions for repurposing of electrodes, and integration of AI-based vision and active machine learning to optimize the efficiency of the process. Writing publications and
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located at SciLifeLab in Stockholm. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in
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systems. Combination of behavior with large-scale neural recordings using silicon probes, miniscope, or 2P imaging. Ability to explore and analyze large datasets using modern machine learning methods and a
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transitions and universality for spectral statistics of random matrices and their applications in high-dimensional statistics, machine learning and probability theory. The Department of Mathematics at KTH
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and machine learning, we collaborate globally to monitor environmental change and support a sustainable future. About the research project The postdoc will work at Chalmers University of Technology in a
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Experience in machine learning Knowledge of SDN and NFV Knowledge of basic TCP/IP protocols What you will do Conduct high-impact research and publish in leading journals and conferences Shape research