SBIR Phase II: AI-Enhanced Career Assessment Tool to Accelerate Student and Professional Access to Emerging Technologies in Web3
- Institution
- CRYPTO TUTORS LLC, FL
- Principal investigator
- Nina Blankenship
- Funding
- $1.3M
- Duration
- 2025–2027
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Abstract
The broader/commercial impact of this SBIR Phase II project is creating new career pathways that empower students and professionals to enter some of the world’s most in-demand industries, accelerating access to cutting edge industries and enabling financial independence. This project also provides hiring managers with access to a wide pool of talent by which to strengthen U.S. companies and catalyze global competitiveness. By addressing the challenges of the rapidly evolving technology space including Web3, this innovative career assessment platform helps individuals navigate career opportunities in blockchain and related fields. The tool clarifies and delineates the process of identifying career paths, required skills, and earning potential, making high-paying roles more accessible to all Americans. By enhancing workforce readiness in emerging industries, the platform is expected to contribute to workforce development and technological leadership in the United States, with a projected significant expansion of qualified professionals within three years. This Small Business Innovation Research (SBIR) Phase II project will address the fact that current career assessments do not include Web3 career recommendations. Millions of university students are graduating and unaware of this high-tech industry. Phase II seeks to deliver a more robust career recommendation engine from hobbies and interests to innovative Web3 careers through a proprietary algorithmic system for entry-level college students, specialized talent, and innovative technology talent, inclusive of job titles related to the following skills–AI, IoT, Zero Trust, Cloud Security, and Machine learning (all used in blockchain technology). The technical hurdles that will be researched are 1. Expanding the dataset with an extension of the current model. 2. Refining the algorithm to include flexibility in handling real-time adaptability 3. Implementing user interface and backend infrastructure to support a large volume of concurrent users and insights. This will become the first to market and fill the needs of both customers with this innovative Web3 career assessment, serving as the bridge between universities and industry. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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