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Field
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generate data that will be used to develop new models of the dissolution and diffusion of different fertilizer formulations. The main responsibilities are: Conduct experiments in the Lab, prepare soil
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theories. Develops advanced analytical models and systems and provides solutions and analyses to support strategic and tactical decisions. Adheres to University and unit-level policies and procedures and
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | 27 minutes ago
, methane, and additives. Oil recovery quantification will include high pressure and temperature laboratory flow tests with rock cores. The participant will also engage with reservoir modeling team to link
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. Who we are looking for The following requirements are mandatory: A doctoral degree (or equivalent foreign degree) in Computer Science, Mathematics, or a related field. This eligibility requirement must
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University of Massachusetts Chan Medical School | Worcester, Massachusetts | United States | about 2 months ago
quantitative skills and curiosity about complex systems. Position Overview You will design, implement, and apply new computational and statistical models to reverse-engineer causal networks from noisy, high
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Science and Engineering Division. The Composites Lab started at KAUST in 2009 and is an integrated environment for composite science, combining modeling and experimental expertise in a single working
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department under the Faculty of Science & Technology at Aarhus University. Our work spans fields from physics, chemistry, microbiology, molecular biol-ogy, and mathematical modeling to social science
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biological and quantitative techniques including microscopy, flow cytometry, computational/mathematical modeling, and utilizes approaches from synthetic biology and complex biological systems. Highly motivated
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activities. Advanced programming skills (HPC), advanced mathematics methods, data analytics techniques and/or Earth system and climate modelling, as well as advanced AI methods. You should also have good
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engineering, hydrology, computational sciences, systems modeling, applied mathematics, or a related field. Preferred Qualifications: Demonstrated expertise in quantitative modeling and data analysis