全球深科技报告2026：深科技创始人：由相似性团结还是由差异驱动？

Contents 1. Executive summary2. Deep Tech relevance & definition3. Dataset & methodology4. Deep Tech startup characteristics5. Deep Tech founding teamcharacteristics6. Deep Tech success factors7. Implications8. Author biographies9. Full citation Contents 1. Executive summary2. Deep Tech relevance & definition3. Dataset & methodology4. Deep Tech startup characteristics5. Deep Tech founding teamcharacteristics6. Deep Tech success factors7. Implications8. Author biographies9. Full citation Executive summary (1/2)1. Executive summary 2. Deep Tech relevance & definitionDeep Tech denotes ventures whose competitive edge is grounded in scientific breakthroughs or engineering challenges, typically combining complex hardware with complex software. All available definitions converge on three shared characteristics: 1) these ventures are rooted in frontier science and engineering, 2) they aresubject to long R&D cycles of roughly 7 to 15 years before commercialization, and 3) they are built on hard-to-imitate intellectual property. Deep Tech startups couldgenerate $1tn in enterprise value plus ~1mn European jobs by 2030. 3. Dataset & methodologyThe study rests on a first-of-its-kind dual dataset 1) 13.6k global Deep Tech startups (5k funding-validated, founded 2015–2024with ≥$100k raised) and 11.5k LinkedIn founder profiles, triangulated acrossDealroom, Pitchbook, Crunchbase, and LinkedIn). 4. Deep Tech startup characteristicsRegional distribution and funding gap.Europe leads the Deep Tech landscape with 6.1k startups, yet the US dominates as the largest country with 4.1k startups. Germany ranks 5th with 0.5k startups, placing it behind the UK (1.1k) and France (0.8k), a structural anomaly given Germany'seconomic weight. Europe accountsfor 45% of global Deep Tech startups but captures only 17% of global Deep Tech funding. The top three Deep Tech funding hubsglobally are San Francisco ($96bn),Palo Alto ($37bn), and Stockholm ($25bn), with Stockholm generating that total from just 99 startups, through exit-driven capital recycling (Spotify, Klarna),Vinnova-backed R&D grants and targeted tax incentives, and a constrained domestic market that forces founders to build globally scalableproducts from day one. The scaling bottleneck.The Series A to Series B conversion rate in Europe is only 10% compared with North America's 24%, and Europe has 81% of its startupsat or below 50 employees versus 68% in North America. North America's M&A exit rate stands at 8%, double Europe's 4%. Patents & sub-industries.North America generates 51% of global Deep Tech patents with only 34% of startups, whereas Europe generates 29% of patents whilehosting 45% of startups. The top three sub-industries are Novel AI (3.9k startups at an average of $44mn), Medtech and Biotechnology (2.4k at $20mn), andSemiconductors and Compute (1.6k at $41mn), while Quantum Technology has the fewest startups but the highest capital intensity at $56mn on average. 5. Deep Tech founding team characteristicsEducation.61% of founders hold either a Master's (4.1k) or a PhD (2.8k), making postgraduate education the baseline rather than the differentiator. The top educational fields are Engineering (3.6k), IT (2.6k), and Management (1.9k). Founder pipelines differ sharply by sector: QuantumTechnology has a 76% PhD rate,indicating it remains a science-push rather than market-pull domain; Novel AI has a 32% Bachelor rate, reflecting the lowest technical barrier to entry of any DeepTech segment. MIT and Stanford dominate the founder-university landscape, with a density of 56 and 35 founders per 1,000 students. Leading European schoolssuch as Cambridge (13 per 1,000) and TUM (3 per 1,000) are an order of magnitude behind MIT. Experience.Leadership experience (5.7k) and founder experience (4.3k) dwarf technical experience among Deep Tech founders, confirming thatDeep Tech is not afirst-time founder game. The top experience organizations include Self-Employed, Google, Microsoft, MIT, Stanford, Intel, and Nokia. Nokia's collapse represents thelargest state-supported corporate-to-startup conversion wave observed. European Deep Tech founders trail their North American peers across three compoundingcredentialing dimensions, prior founding experience (36% vs 43%), prior Deep Tech experience (24% vs 33%), and top-10 universityattendance (14% vs 29%). Executive summary (2/2)1. Executive summary 6. Deep Tech success factorsFounder human capital.Technical education in IT and Natural Sciences and management experience are the two strongest positive predictors of both capital raised and valuation. Management education carries a negative coefficient on capital, and technical experience on its own hasnosignificant effect, showing thatapplied technical depth combined with operational managerial tenure increases Deep Tech success. Management experience peaksatroughly 18.3 years beforediminishing returns set in, engineering experience peaks much earlier at around 5.3 years, and