ORAU
Adapting Machine Learning for Army Research and Sustainability
ORAU, Aberdeen, Maryland, United States, 21001
Adapting Machine Learning for Army Research and Sustainability
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Adapting Machine Learning for Army Research and Sustainability
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ORAU . Overview
Data collected from Army research projects and systems testing is varied and often different from canonical data used to benchmark machine learning (ML) algorithms. This opportunity will evaluate how state-of-the-art ML techniques can extract and predict meaningful information from Army-relevant data, and develop data preprocessing and analysis strategies to collaborate with research/test communities and advance ML applicability in non-canonical domains. About the Research
Data from Army projects and testing is varied; the goal is to apply ML to extract meaningful information and develop preprocessing/analysis strategies for collaboration and broader ML applicability. Organization
DEVCOM Army Research Laboratory Reference Code
ARL-R-CISD-3590623109-NCCS Description
About NCCS: Sciences to enable and ensure secure resilient communication networks for distributed analytics in Multi-Domain Operations. About ARL RAP
The Army Research Laboratory Research Associateship Program (ARL-RAP) increases involvement of scientists and engineers from academia and industry in Army-relevant research areas, including applied mathematics, signal processing, chemistry, computational and information sciences, and more. About Army Research Directorate (ARD)
ARD focuses on exploiting concept development, discovery, technology development, and transition to deliver advantageous science-based capabilities and manages essential flagship research programs. A Complete Application Includes
Curriculum Vitae or Resume Three References Forms Transcripts Additional reference information (as applicable) References
References should be from persons familiar with your qualifications (include your thesis or dissertation advisor, if applicable). An email with a link to the reference form will be provided in Zintellect upon application completion. Proposal
If selected by an advisor, you will be required to write a research proposal for ARL-RAP review, addressing: Relation to a specific ARL opportunity Clear objective and defined outcome Planned direction and expected completion period Brief background and motivation References of published efforts may be used to support the proposal A link to upload the proposal will be provided after advisor selection. Questions
Please email ARLFellowship@orau.org Point of Contact
ARL Eligibility Requirements
Citizenship: U.S. Citizen Only Degree: Master's Degree or Doctoral Degree Academic Level(s): Any academic level Discipline(s): Chemistry and Materials Sciences; Analytical Chemistry; Bio-inorganic Chemistry; Bio-organic Chemistry; Biophysical Chemistry; Chemistry (General); Environmental Chemistry; Inorganic Chemistry; Materials Sciences; Organic Chemistry; Physical Chemistry; Polymer Chemistry; Theoretical Chemistry; Engineering; Mathematics and Statistics; Physics; Science & Engineering-related Age: Must be 18 years of age
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Join to apply for the
Adapting Machine Learning for Army Research and Sustainability
role at
ORAU . Overview
Data collected from Army research projects and systems testing is varied and often different from canonical data used to benchmark machine learning (ML) algorithms. This opportunity will evaluate how state-of-the-art ML techniques can extract and predict meaningful information from Army-relevant data, and develop data preprocessing and analysis strategies to collaborate with research/test communities and advance ML applicability in non-canonical domains. About the Research
Data from Army projects and testing is varied; the goal is to apply ML to extract meaningful information and develop preprocessing/analysis strategies for collaboration and broader ML applicability. Organization
DEVCOM Army Research Laboratory Reference Code
ARL-R-CISD-3590623109-NCCS Description
About NCCS: Sciences to enable and ensure secure resilient communication networks for distributed analytics in Multi-Domain Operations. About ARL RAP
The Army Research Laboratory Research Associateship Program (ARL-RAP) increases involvement of scientists and engineers from academia and industry in Army-relevant research areas, including applied mathematics, signal processing, chemistry, computational and information sciences, and more. About Army Research Directorate (ARD)
ARD focuses on exploiting concept development, discovery, technology development, and transition to deliver advantageous science-based capabilities and manages essential flagship research programs. A Complete Application Includes
Curriculum Vitae or Resume Three References Forms Transcripts Additional reference information (as applicable) References
References should be from persons familiar with your qualifications (include your thesis or dissertation advisor, if applicable). An email with a link to the reference form will be provided in Zintellect upon application completion. Proposal
If selected by an advisor, you will be required to write a research proposal for ARL-RAP review, addressing: Relation to a specific ARL opportunity Clear objective and defined outcome Planned direction and expected completion period Brief background and motivation References of published efforts may be used to support the proposal A link to upload the proposal will be provided after advisor selection. Questions
Please email ARLFellowship@orau.org Point of Contact
ARL Eligibility Requirements
Citizenship: U.S. Citizen Only Degree: Master's Degree or Doctoral Degree Academic Level(s): Any academic level Discipline(s): Chemistry and Materials Sciences; Analytical Chemistry; Bio-inorganic Chemistry; Bio-organic Chemistry; Biophysical Chemistry; Chemistry (General); Environmental Chemistry; Inorganic Chemistry; Materials Sciences; Organic Chemistry; Physical Chemistry; Polymer Chemistry; Theoretical Chemistry; Engineering; Mathematics and Statistics; Physics; Science & Engineering-related Age: Must be 18 years of age
#J-18808-Ljbffr