23 structures-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"L2CM" positions at Zintellect
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virulence monitoring of domestic and international isolates. The research project entails using artificial intelligence-based structural modelling to predict plant-pathogen protein-protein interactions
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) Engineer Research and Development Center (ERDC) Construction Engineering Research Laboratory (CERL) develops and infuses innovative technologies to provide excellent facilities and realistic training lands
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waste disposal facilities. An interactive dashboard of current IHS Division of Sanitation Facilities Construction BIL/IIJA projects can be found at https://dsfc-ihs-gis.hub.arcgis.com/ and additional
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discoveries through scientific excellence. Research Project: Research will focus on development of bioinformatics and genomics tools to characterize the structure and function of the bovine genome and then
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forest conditions and analyze the effects of those insect and disease agents on attributes such as ecological integrity, including metrics related to forest structure, species composition, and biodiversity
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Description A Ph.D. degreed chemical engineer or materials chemist is sought to work on the densification and characterization of solid-state battery materials including argyrodite and spinel structured
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research activities and gain experience working within an academic laboratory environment alongside team members with varied levels of experience. You will receive structured mentorship and guidance
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advantageous. Additional preference will be given to candidates with computational experience in protein structure–function prediction, metabolic or biochemical pathway analysis, machine learning applications in
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analysis experience and scientific writing ability Experience with systematic or scoping reviews (or other structured knowledge-synthesis methods) Experience in R or Stata Knowledge of experimental and
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structure among and between accessions in the collection The development of a genetically representative core collection Correct accession taxonomic assignments Redundancy identification leading