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DEVCOM Army Research Laboratory

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Learning-based Modeling Approach for Information Asset Valuation and Selection DEVCOM Army Research Laboratory in United States

Degree Level

Master's, Postdoc

Field of study

Computer Science

Funding

Available

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Country

United States

University

DEVCOM Army Research Laboratory

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Keywords

Computer Science
Information Technology
Mathematics
Artificial Intelligence
Statistical Inference
Geometric Modeling
Optimisation
Data Streams
Computational Modelling
High-dimensional Data
Statistics
ML

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About this position

This research opportunity at DEVCOM Army Research Laboratory focuses on developing novel methods for information asset selection and content filtering from high-dimensional data. The project asks the researcher to build and validate context-aware, adaptive learning models that can identify the most relevant and valuable information assets in high-dimensional streaming data.

The work emphasizes the use of state-of-the-art machine learning methods that can adapt dynamically to human or agent actions and to changing contextual situations and environments. A further part of the project is to develop approaches for quantifying confidence in the models, supporting more reliable decision-making from data-rich streams.

The opportunity is embedded in the Army Research Laboratory’s research environment, where scientists and engineers contribute to advanced science and technology topics including computational and information sciences. The project is advised by Jade Freeman with co-advisory support from Jesse M Milzman.

Funding details

Available

What's required

Degree: Master's Degree or Doctoral Degree. Academic level(s) mentioned include Master’s Degree (Journeyman Fellow), Master’s Degree 7+ years (Senior Fellow), Doctoral Degree (Postdoctoral Fellow), or Doctoral Degree 5+ years (Senior Fellow). Applicants must be at least 18 years old. A complete application requires a CV or resume, a list of relevant coursework and lab experience plus any papers/presentations/publications and reprints or abstracts if available, three reference forms, transcripts verifying receipt of degree or current enrollment in an undergraduate or graduate program at an accredited university or technical institute (student/unofficial copy acceptable), and a research proposal with a clear objective, defined outcome, planned direction, expected study period, brief background, and motivation.

How to apply

Submit the application in Zintellect. After completing the online application, send the reference-form email link to your selected referees so they can complete the forms. Upload the required CV, transcripts, reference information, and research proposal with the application.

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