Technology Ventures & Commercialization Associate

Fujitsu Research; Bengaluru; Híbrido; INR 900.000 - 1.500.000; Tempo integral

Resumo da vaga

Fujitsu Research India, FRIPL is seeking a Technology Ventures & Commercialization Associate for a 12-month role to translate advanced research into startup opportunities. You will work with researchers to identify use cases, assess startup fit, and support PoCs and partnerships to drive commercialization.

This position suits candidates with a strong technical background and interest in entrepreneurship and technology transfer.

Qualificações

• M.Tech / MS or equivalent postgraduate degree in CS, AI/ML, Data Science, or related fields.
• Strong ability to reason technically and learn new technologies quickly.
• Interest in startups, deeptech, productization, and commercialization.
• Excellent ability to communicate technical concepts to business stakeholders.
• Exposure to research projects, prototypes, or innovation programs is advantageous.

Responsabilidades

• Understand Fujitsu research technologies and their potential applications.
• Identify industry problems and startup partners for differentiated value.
• Assess startup-technology fit and data or infrastructure needs.
• Support PoCs, sandbox experiments, and validation with defined criteria.
• Shape commercialization pathways like licensing, cocreation, or partnerships.
• Prepare technology briefs, evaluation notes, and management-ready recommendations.

Conhecimentos

Strong technical reasoning

Communication with business

Startup/commercialization interest

Analytical problem solving

Formação

M.Tech / MS / equivalent

Descrição da vaga

Fujitsu Research India, FRIPL

Technology Ventures & Commercialization Associate

Duration : 12 months

Role & responsibilities

About the Role Fujitsu Research India is seeking a technically strong associate to help translate advanced research technologies into real-world startup and market opportunities. The role combines technology understanding, use-case discovery, startup fit assessment, validation support, and commercialization thinking. It is suited to an M.Tech/MS candidate who is curious about both how technology works and how it can create business value.

Key Responsibilities

• Understand selected Fujitsu research technologies, their differentiation, maturity, limitations, and potential applications.
• Identify industry problems, use cases, startups, and partners where these technologies could create differentiated value.
• Assess startuptechnology fit, including technical compatibility, integration feasibility, data or infrastructure needs, and adoption readiness.
• Support PoCs, sandbox experiments, and technical validation by defining success criteria, dependencies, risks, and evidence required for progression.
• Work with researchers and incubation teams to shape commercialization pathways such as licensing, joint development, cocreation, startup-led adoption, or strategic partnerships.
• Prepare concise technology briefs, evaluation notes, opportunity maps, validation summaries, and management-ready recommendations.

Ideal Candidate

• M.Tech / MS / equivalent postgraduate degree in Computer Science, AI/ML, Data Science, Electronics, Robotics, Quantum, Cybersecurity, Computational Science, or a related field.
• Strong technical reasoning with the ability to understand unfamiliar technologies quickly.
• Interest in startups, deeptech, productization, entrepreneurship, and technology commercialization.
• Ability to communicate technical concepts clearly to business and external stakeholders.
• Exposure to research projects, prototypes, startup projects, hackathons, publications, patents, or innovation programs is an advantage.
• Structured, self-driven, analytical, and comfortable working on exploratory problems.
• Expected Outcomes
• Technology-to-use-case and technology-to-market opportunity maps.
• Startuptechnology fit assessments and shortlisted collaboration opportunities.
• PoC / validation plans and evidence-based outcome summaries.
• Commercialization-readiness recommendations for selected research technologies.