Venture Scientists: Commercialising Research with Conception X

Venture Scientists: Commercialising Research with Conception X

In this week’s guest blog post, Aurora Percannella, the Digital Marketing Lead at Conception X, writes about her work at a the not-for-profit organisation supporting PhD researchers interested in commercialising their research, and shares details about their nine-month programme for PhD students.

The day after the US Food and Drug Administration set out to ban flavoured e-cigarettes, a campaign targeting key policymakers to persuade them to withdraw anti-vaping legislation spread across Twitter, under the hashtags #WeVapeWeVote and #IVapeIVote. 

Astroscreen, a British startup that uses machine learning to detect disinformation campaigns, conspiracy theories and election interference, found that a quarter of the tweets came from fake accounts and had managed to get past Twitter’s spam detection algorithm. While in this instance the impact of the campaign was minimal, it highlighted the potential for these types of operations. Since then, Astroscreen’s founder Ali Tehrani has further refined his technology and has made the Forbes 30 Under 30 Europe 2021 list.

Since launching three years ago, Conception X has trained more than 160 PhD deeptech startups like Astroscreen, supporting students from leading universities in their journey from researchers to founders – or venture scientists, as we prefer to call them. 

“It’s our terminology for a scientific founder,” Conception X CEO Riam Kanso says. “We want to emphasise we’re not changing PhD students’ identity to become business people; they should continue to do what they do best but with a commercial mindset.”

Our venture scientists have gone on to develop world-leading quantum machine learning solutions for drug discovery, spark global conversations on the future of AI and art, use machine learning to detect disinformation, conspiracy theories and election interference, design new wind turbines that can help bring down the cost of clean energy, develop complex low-memory machine learning technology with key implications for conservation projects, and more

Tech for good lies at the heart of what we do, and so does the idea that we need to encourage future innovators to get off the beaten tracks of traditional careers that are expected of them, developing solutions to urgent problems such as climate change, automation, cybersecurity threats, the future of health. 

Our nine-month programme meets PhD students where they are. It supports them in applying their technical knowledge and research to launch deeptech startups through a combination of entrepreneurship training designed for scientists and engineers, one-to-one business and technology coaching sessions, and introductions to our network of experts, investors and academics. 

We made the conscious decision to design a free programme that fits around PhD students’ busy research schedules, where the university is the incubator and the thesis – rather than a project on the side – becomes the basis for a deeptech startup. This way, we de-risk experimentation for our venture scientists as much as possible. We also take no equity. This allows us to take on groundbreaking ideas and bold projects that other programmes wouldn’t touch because of their inherently risky nature. 

If you’re interested in applying, we’ve just started recruiting for Cohort V, which will start in March 2022. Find out more about the programme on our website and submit your application by 28 January 2022. 

We also run monthly Discovery Sessions online for PhD students to meet the team, listen to recent alumni, and find out whether the programme is for them. Register via Eventbrite