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10 Crosscutting Recommendations
Pages 108-110

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From page 108...
... For example, many of the projects increasingly employ advanced computational science, including multiscale materials simulations, deep learning algorithms, and multi-agent optimization, for which external expertise would be impactful and when expertise developed via ILIR projects could help others. It appeared that many of the best ILIR projects created synergies with and benefitted from external scientific input, while some of the projects that were less successful appeared to lack such helpful inputs and consequently made less progress.
From page 109...
... Metrics reflect to a significant degree issues of efficient research management, including setting strategic scope, planning and securing future funding, training staff, and evaluating staff progress in reaching goals by rational critical paths within consistent evaluation criteria. There is sometimes a competition for limited resources that drives the directions of research to meet niche Army needs without sacrificing broader scientific justification.
From page 110...
... It was not apparent that sufficient oversight was provided to ensure effective utilization and leverage of these limited resources to maximize the overall impact of each project. In addition, although future plans were discussed, it was not clear how to assure successful execution to completion given changes in the investigators' team membership or availability of research infrastructure.


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