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. Applicants should demonstrate expertise in programming languages such as Python and/or R, as well as experience working with high-performance computing clusters. The successful candidate will be a team player
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is part of the Maersk Mc-Kinney Moller Institute , University of Southern Denmark (SDU), and located at the main Campus in Odense, at the core of the Odense Robotics Cluster involving 120+ startups
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developing and implementing very large deep learning models. Familiarity with high performance computing environments (e.g., HPC clusters, GPUs, Cloud resources) and managing Linux based hardware systems
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access to world-class computing resources, such as the BNL Institutional Cluster and DOE leadership computing facilities. Access to these platforms will allow computing at scale, and together with access
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these applications to inform new foundational ML and NLP innovations. The position provides unique access to world-class computing resources, such as the BNL Institutional Cluster and DOE leadership computing
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Cluster and DOE leadership computing facilities. Access to these platforms will allow computing at scale, and together with access to unique data sources, will ensure that the successful candidate has
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. Developing bottom cells at different scales (from 1 by 1 cm2 to 6 by 6 inch2) utilizing the PECVD-PVD cluster. Performing device characterization, and modeling aimed at champion PCEs. Manage project tasks
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and uses these applications to inform new foundational ML and NLP innovations. The position provides unique access to world-class computing resources, such as the BNL Institutional Cluster and DOE
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Summary The primary research focus is the role of cell adhesion and neuronal self-avoidance in the developing mouse retina, focusing on two families of cell adhesion molecules: the clustered
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-years to better understand innovation clusters and how to accelerate the quantity and quality of innovation output and their economic and social impact. This team will conduct research as part of