A challenge that supports you at every step

The Postdoc Venture Creation Challenge, (PVCC) is aimed at supporting busy University of Cambridge postdocs interested in taking their first steps into creating a venture from their research.

The challenge welcomes innovative ideas across deep tech, life sciences, AI, software, and social impact.

Previous winners of the PVCC have gone on to raise £172m in investments and the programme represents a unique chance to get your early ventures recognised and developed.

More than a competition the PVCC, provides workshops, mentoring and an incredible launchpad for early-stage ideas.

2026 Semi-finalists

Camentis

Camentis is developing a construction technology platform that brings together information from site cameras, delivery records, labour returns, programmes and daily reports. By connecting data that currently sits across separate systems, the team aims to provide an integrated view of activity on construction sites, increasing efficiencies and reducing carbon emissions.

Team: Ashan Asmone (lead); Danny Murguia

CardiOn Therapeutics

CardiOn Therapeutics’ mRNA-based regenerative therapy stimulates significant proliferation of adult heart cells – a breakthrough previously considered unattainable. With validated in vivo proof-of-concept, their approach provides a scalable, non-surgical solution to re-muscularise failing hearts and restore functional capacity to millions of patients.

Team: Jin Seok Lee (lead); Catherine Wilson

Cattleya Bio

Cattleya Bio is developing a computational platform to support treatment decisions for Mycobacterium avium complex lung disease. The proposed approach brings together pathogen, patient and clinical information to help identify which patients may be less likely to respond to treatment, so care can be adapted and patient outcomes improved.

Team: Julieth Murillo Silva (lead); Paniz Hosseini; Santiago Fragoso

ChromaNova AI

ChromaNova AI is creating an AI discovery platform for safer, high-performance colourants, where the team wants to support the discovery and development of new colourant candidates. Its initial focus is on textiles and related materials markets with the aim of reducing clean water pollution.

Team: Mehrdad Asgari and Soheila Kookalani (co-leads); Dhruv Menon; Angelo Di Bella

DroplexBio

DroplexBio is developing droplet-based methods to produce commercially valuable proteins that are difficult to manufacture in bacteria. The team’s approach is intended to offer an alternative to existing methods that can be costly, complex or difficult to scale.

Team: Brian Ng (lead); Catherine Fan; Lorenzo Di Michele

FluiStat

FluiStat is developing a wearable sweat-sensing patch that continuously monitors body chemistry during exercise. The product is designed to collect information without needles, blood samples or any action from the wearer.

Team: Demi Zhang (lead); Tom Wade; Thiyagarajan Natarajan; Sohini Kar-Narayan

Haptos Technology

Haptos Technology is developing a flexible electronic skin that gives robots a sensitive sense of touch, enabling them to detect pressure, temperature, texture and slip in real time. This could improve robotic dexterity and safety in manufacturing, agriculture and healthcare.

Team: Zhuo Chen (lead); Tawfique Hasan; Doga Doganay; Madhurjot Sohi; Amir Nateghi

Hearnest

Hearnest is developing an AI companion for pregnancy and postpartum. It aims to turn everyday experiences into care-ready insights, supporting women and families between appointments and enabling more informed conversations with healthcare professionals.

Team: Yang Liu (lead)

Loom Light

Loom Light is developing a platform focused on grid-risk pricing for renewable energy projects. The venture aims to help investors, insurers and developers assess project risk more effectively and support more informed financing decisions.

Team: Deepanshu Kush (lead); Leonie Mueck; Kyrill Borzenko

MetCycle

MetCycle is developing a process to recover critical metals from spent batteries. The venture aims to support a more circular supply chain for electric vehicles and energy storage while reducing reliance on newly mined materials.

Team: Esther Gray (lead); Manish Chhowalla; Javier Rubio Garcia

Multi-View Learning Stratifier

Multi-View Learning Stratifier is developing a clinical-trial stratification platform for ovarian cancer. It uses whole-genome and multi-view biological data to identify more meaningful patient groups, with the aim of supporting better trial design and interpretation.

Team: Gabriel Funingana (lead); Michael Gill; James Brenton

Omniscia

Omniscia is developing an AI-enabled tool for spatial biology analysis. It is intended to help researchers interpret complex imaging and molecular data more efficiently and make advanced analysis more accessible to teams without dedicated in-house expertise. They will begin with cancer tissue analysis.

Team: Qiuchen Meng (lead); Kui Hua; Wenchang Chen

PeatWaterWise

PeatWaterWise is developing AI powered monitoring tools to support peatland water management. By helping users optimise water-table depth, the venture aims to reduce carbon emissions while supporting sustainable agricultural land use.

Team: Neha Joshi (lead); Hamidreza Rahimi