When Tech Transfer Offices (TTOs) evaluate a newly developed scientific instrument, the conversation naturally centers on intellectual property. Who owns the foreground IP? Are there existing background patents? Can we secure a broad enough claim to attract investors?
While managing IP is critical, focusing strictly on the patents ignores the most fragile and valuable asset in the entire valorisation process: the human capital.
The PhD candidate or postdoc who spent four years painstakingly building, wiring, and calibrating that bench prototype holds the tacit knowledge required to commercialize it. Yet, the traditional university system offers them very few viable deep tech career pathways. When these researchers inevitably graduate, the region faces a massive brain drain. To build a resilient innovation ecosystem, TTOs must look beyond just licensing patents and take an active role in creating structured commercial pathways for their top engineering talent.
The Problem: A Lack of Viable Pathways
Currently, when a brilliant opto-mechanical engineer or microfluidics expert finishes their academic project, they are presented with a highly flawed set of options:
- The Academic Loop: Stay on for another short-term postdoc grant, continuously patching their original prototype for new experiments, but never scaling it.
- The Forced CEO Route: Accept the TTO’s offer to spin off a venture-backed startup. This forces an engineer to instantly become a CEO, pitch to VCs for a niche instrument with a small TAM, and take on massive personal financial risk.
- The Corporate Pivot: Abandon hardware altogether. Because there is no structured middle ground, these highly trained researchers accept lucrative, low-risk jobs as data scientists or standard software engineers at large tech firms.
Option 3 is the most common outcome. The researcher leaves, the tacit knowledge is lost, and the IP effectively dies on the bench.
Empowering the "Valorising Agent"
To stop this exodus, TTOs must stop viewing commercialization as an entirely separate endeavor from talent development. We need to rethink transitioning from academic bench to industry not as a leap off a cliff into the startup world, but as a deliberate, supported phase of engineering.
Instead of pressuring researchers to become startup founders, TTOs can partner with external productization studios to offer these postdocs a role as a dedicated "valorising agent."
In this model, the grant requirements for "Knowledge Utilization" are no longer just bureaucratic boxes to check. The researcher is actively hired by a productization partner for a dedicated sprint. Their explicit, full-time mandate is to act as the agent of translation—porting their novel scientific breakthrough into a pre-existing, commercial-grade hardware and software architecture.
Retaining Academic Hardware Engineers
By utilizing a centralized productization engine, TTOs can offer postdocs a zero-risk, high-impact bridge into the commercial sector.
During this productization sprint, the researcher receives a competitive salary and works alongside veteran systems engineers. They do not have to worry about cap tables or seed funding. Instead, they focus entirely on clearing the "Platform Tax." They learn how to translate fragmented LabVIEW scripts into production-ready Python/PyQt architecture, how to navigate CE-marking requirements, and how to utilize a shared supply chain of modular enclosures.
This model is the ultimate tool for retaining academic hardware engineers within the regional ecosystem.
At the end of the sprint, the TTO has successfully commercialized the university's IP, generating a reliable, globally deployable asset. Simultaneously, the region has gained a seasoned, commercially hardened deep tech engineer. Whether that researcher decides to stay with the product studio, transition into a senior role within a major European high-tech manufacturer, or even return to academia, their specialized talent remains within the ecosystem.
True valorisation goes beyond commercializing technology; it means commercializing the talent capable of building the next generation of deep tech.