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congress and information booths · Contributing to the execution of omnichannel and digital strategy within Medical Affairs to ensure optimal orchestration of scientific information to key stakeholders
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to optimize scientific quality/innovation of clinical study design, execution, reporting and publication. · Contribute to trial-related advisory boards. · Participate in investigators meetings and
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outcomes using both imaging and molecular biology methods including confocal microscopy and RNAscope Design and conduct any downstream, secondary assays for hit validation and lead optimization. Work with
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research project, where you will be part of the research team to develop solutions for adapting CCS2 chargers for marine electrical vessels and optimizing DC fast charging technology for marine applications
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. The position is part of a small team that works on the development and optimization of algorithms for these problems, as well as proofs on theoretical complexity bounds. Common tasks include: Developing ideas
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the increasing use of recycled asphalt binders in new pavements. Under the guidance of a mentor, the participant will participate in the development and optimization of chemical processes to improve
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Article 3 of FCT Fellowship Regulation. Work Plan and Objectives - Maintain human skeletal muscle cell line cultures; - Develop and optimize molecular and cellular biology protocols (e.g., cloning, Western
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
research challenges in: dynamical systems differential games optimal control numerical optimisation and/or machine learning in control About the opportunity The successful applicant will become part of a
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and optimization of algorithms for these problems, as well as proofs on theoretical complexity bounds. Common tasks include: Developing ideas for improving existent or creating novel algorithms Coding
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the industry to lead and/or conduct innovative research on, but not limited to evolutionary computing, job scheduling, transfer optimization, transfer learning, reinforcement learning, large-scale