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, providing a platform to identify and optimize therapeutic candidates. Our group specializes in developing technologies to assess the multicellular environment within three-dimensional microtumor models
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thermoplastic feedstocks for FDM printing Programming of an existing hybrid FDM printing machine, including printing and milling devices Modelling and optimization of the debinding process Simulation-based design
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
Vision is to use scientific discovery to ensure optimal health through individualized nutrition. Everyone who works at the NRI supports this hopeful vision. Working at the NRI means doing good
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-off companies. CONTEXT AND MISSION We are seeking a postdoc to join the Quantum Machine Learning team (QML-CVC) in beautiful Barcelona. The QML-CVC team (https://qml.cvc.uab.es /) is part of
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of the urban soil/subsoil in Amsterdam required for optimal tree growth. Ecosystem services include: storing water in the unsaturated zone; draining water via groundwater; sequestering carbon; filtering and
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inorganic syntheses Develop and optimize electrochemical experiments and measurements Characterize materials and compounds using standard analytical techniques Analyse data and document results Collaborate
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experimental independence, including the design and execution of animal studies, development and optimization of molecular and cellular assays, and data analysis and interpretation. Candidates should be
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, Sputtering or MOCVD systems for microelectronics and emerging sensor technologies. Key Responsibilities: Develop and optimize wafer-scale 2D materials, including TMDCs, MXenes, and MOFs, for microelectronics
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an autonomous framework for setting up, executing, and optimizing complex electronic structure workflows, ranging from ground-state Density Functional Theory (DFT) to many-body perturbation theory methods such as
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) or discrete manufacturing (e.g., electronics assembly, automotive, home appliances). Explore the integration of large language models and reinforcement learning for real-time optimization, fault self