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, presentations, and research reports based on appropriate application of theories and analysis of the research data. Research Field Support: Contribute to the design of the research. As needed, assist in data
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research helps overcome common implementation barriers to nature-based solutions projects by identifying economic, environmental, and community assets using multiple data sources and spatial tools. The role
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Job Description Applications are invited for a National Science Foundation funded (LEAP HI Program #2051685), Postdoctoral Associate position with the System Performance Laboratory (SPL
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Institute of Metabolic and Cardiovascular Diseases (Toulouse) | Toulouse, Midi Pyrenees | France | about 9 hours ago
interdisciplinary research, including the use of generative AI in medicine for dataset analysis Proficiency in R Personal qualities: Personal suitability, good communication and teamwork skills, inventiveness, and a
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, operate at higher temperatures (1450°C ≈ 2700°F), and have longer lifespans. The study presented here focuses on the development of CMCs based on the silicon-carbon-nitrogen (Si-C-N) ternary system
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. Experience in integrated modelling simulations would help. Experience in numerics: use of parallelised codes, programming (Fortran/C), use of analysis tools like Matlab or Python Website for additional job
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, the Brazilian national public health network), with an analysis of cancer care maps in the health regions of São Paulo and related training processes. This project is carried out by the University of São Paulo's
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or pain research, and proficiency with imaging or data-analysis software. Strong communication skills, the ability to work independently and collaboratively. This position is eligible for visa sponsorship
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points) Development of bioinformatics tools for biological image analysis (5 points) Programming skills (5 points) Ability to work independently and remotely (5 points) Experience in computational analysis
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analysis of data from the ATLAS experiment. The L2IT team plays a leading role within the ATLAS collaboration in the reconstruction of charged particle tracks using geometric deep learning (GDL). The person