22 computational-drug-design Postdoctoral research jobs at King Abdullah University of Science and Technology in Saudi Arabia
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. Collaboration with clinicians and biologists. Active participation in the development of the projects (e.g. design, conceptual development, etc) Collaborate with the development of any bioinformatic development
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the current storage and transportation technologies, to which we believe adequately engineered and designed thermoplastic carbon fiber technology can be beneficial. The project will be organized around 3 main
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research activities, including experiment design, execution, and troubleshooting. Publish research findings in high-impact journals and present at international conferences. Compensation Package: Competitive
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are insufficient. We believe it requires radically new approaches to realize the full potential of viral vector gene therapy and democratize these technologies in precision medicines. With an innovation ecosystem
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topics. Candidates should have some experience working with FPGAs as well as an understanding of computer networks. Experience with both RTL and HLS design is favoured. The ideal candidate would have some
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. · Collaborate with interdisciplinary teams, including chemists, material scientists, and engineers. · Manage day-to-day research activities, including experiment design, execution, and troubleshooting
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engineering. Plan and execute research tasks, analyzing data, publishing findings in peer-reviewed journals, and presenting research at scientific conferences. May participate in the development of patent
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for the following research themes: Heterogeneous Catalysis Metal Capture from Water Electrochemical Water Splitting Process Design and Scale-up
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, merit-based research university dedicated to advancing scientific and technological education and research, acting as a catalyst for innovation, economic development and social prosperity in the region
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-inspired approaches for modeling, designing, and predicting the response of composite systems. Responsibilities: Develop AI approaches for predictive multi-physics response of composites in Energy