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DoD Communities of Interest: R&D Research and Development Subject: Identifying and Enabling Emerging Technology Leaders Due Date: May 24, 2021 04:00 pm EDT Government Organization: Army Rapid Capabilities and Critical Technologies Office (RCCTO) Description: The Army is supporting the identification and development of a new class of “Emerging Technology Leaders” (ETLs). An ETL is a uniformed expert who serves as the interface between the Army's operational community and the technical community (i.e. scientists, engineers, and technologists). The Army seeks research solutions leveraging data science and/or machine learning techniques that will revolutionize how the Army recruits, develops, selects, and distributes talent across the force. The Army seeks a software and/or data analytics tool that provides robust recommendations for critical ETL selection and recommendation criteria, including: Skill identification: Unbiased identification and estimation of an individual’s skills based on standard CV/resume input; Identification and estimation of a job’s required skills based on a job description. Talent Recruitment: Strategies for targeting specific workforce sectors with prescribed sectors of elite talent. Talent Selection: Unbiased assessment and comparison regarding the applicability of certain skillsets as compared to workforce requirements. Talent Development: Tell individuals what their skill deficiencies are and what jobs/opportunities would increase those skills; and Talent Distribution: Predictive analytics for optimizing the distribution of civilian/military/contractor talent across the force. Any submissions should be able to explain (in math, code, and/or theory) how skill identification and career planning capabilities work, demonstrate these functions with novel data, and identify limitations of the product (technical or data related). PHASE I: Develop operational concept and construct for theory, mathematics, and/or algorithms that inform Emerging Technology Leader (ETL) identification, recruitment, selection, development, and deployment/distribution. The Phase I deliverable should explain the algorithms, software concepts, potential use cases, and potential limitations for applicability within the Army. PHASE II: Develop and demonstrate a technically feasible software prototype that showcases how the solution addresses the challenges described in the DESCRIPTION of this topic and meets or exceeds the OBJECTIVE of this topic. The demonstration shall show the prototype as a proof-of-concept in a form-factor compatible with Army uniformed officer staffing and deployment decisions. PHASE III: This SBIR would integrate software analytics and machine learning algorithms as a pathfinder initiative, highlighting the reduction of workload requirements for manual staffing decisions enabled by integrated machine learning, neural network algorithms, and/or other data analytic techniques. Dual-use should consider applications in the hi-tech business sector. Additional information can be found at the enclosed link to beta.SAM.gov. Website: https://beta.sam.gov/opp/f269df120e854b1ea874df51b9f3ec5e/view |
Army Rapid Capabilities and Critical Technologies Office (RCCTO) Identifying and Enabling Emerging Technology Leaders
SUSPENSE: May 24, 2021 Description: The Army is supporting the identification and development of a new class of “Emerging Technology Leaders” (ETLs). An ETL is a uniformed expert who serves as the interface between the Army's operational community and the technical community (i.e. scientists, engineers, and technologists). The Army seeks research solutions leveraging data science and/or machine learning techniques that will revolutionize how the Army recruits, develops, selects, and distributes talent across the force.