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Field
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project is carried out in collaboration withthe department of Architecture and Civil Engineering, Danmarks Tekniske Universitet (DTU, Denmark) and Universidad del Desarrollo / ISI Foundation (Chile/Italy
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the genetic architecture of molecular traits alone and in interaction with the environment. S(h)e will help in defining the direction of scientific work, conducting research, analyzing data, preparing the work
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/Responsibilities: Design and implement a modular ROS 2 software architecture for onboard sensing, autonomy, mapping, data logging, launch management, and configuration management. Develop and integrate ROS 2 drivers
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cavity layouts using industry-standard simulation software (e.g., COMSOL Multiphysics, Ansys Lumerical FDTD). Analyze complex experimental data and utilize insights to iteratively optimize device
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materials into Retrieval Augmented Generation (RAG) architectures and customized AI assistants. coordinating collaboration among faculty members, technical partners, innovation support units, and partner
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following skills: Strong interest in the field of neuroimaging, psychiatry and genetics. Computer skills: Strong level in the main informatics software (FSL, Freesurfer, fMRIprep) and coding languages (R
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. Experience with 5G or 6G transport, Xhaul, network slicing, SDN, or software-based network control. Familiarity with network modeling and simulation tools and with resilience and reliability metrics
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. Experience with 5G or 6G transport, Xhaul, network slicing, SDN, or software-based network control. Familiarity with network modeling and simulation tools and with resilience and reliability metrics
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deep learning including data collection, architecture development, model training, and validation Interest in software development, with particular emphasis on the Python programming language and
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Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | 2 months ago
on LazySlide ( et al Nature Methods ), our scalable software foundation, and our deep learning framework for age prediction (Abila et al., Nature Medicine, in press) to engineer a body-scale machine learning