Spinout First Light Fusion raises £22.7m
First Light Fusion, spun out from the University of Oxford with help from Oxford University Innovation, has raised £22.7m million to develop process for achieving practical and affordable fusion energy.
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First Light Fusion, spun out from the University of Oxford with help from Oxford University Innovation, has raised £22.7m million to develop process for achieving practical and affordable fusion energy.
Oxford Sciences Innovation, which will provide capital and scaling expertise to Oxford spinouts, has now raised £320m from investors including billionaire Charles Dunstone, who launched Carphone Warehouse, and Google Ventures.
Oxford University researchers have found a promising future treatment for heart disease, going back to a drug first developed in 1950.
Every expectant mother is familiar with the “Sonicaid” – a hand-held monitor used to “hear” the foetal heart beat, monitoring the baby’s health and detecting any early signs of distress in pregnancy. What many don’t realise is that the technology used in some of the “Sonicaid” range of fetal monitors includes the comprehensive heartbeat and fetal movement (cardiotocograph or CTG) analytics developed and refined by University of Oxford Professors Geoffrey Dawes and Christopher Redman.
The first ever event for investors to learn about prospective spin-out companies from both the Universities of Oxford and Cambridge was held at the London Stock Exchange last week.
TheySay, spun out by Oxford University Innovation in 2011, is an advanced text and sentiment analytics company.
Roy Azoulay of the Isis Software Incubator offers an update on Oxford's startup successes in 2015 in TechCityInsider.
Breakthrough technology automates analysis of CT brain scans to support doctors in making life-saving treatment decisions
The Royal Academy of Engineering has announced that Oxford's Dr Peiman Hosseini is one of four finalists winning funding, mentoring and support from the Academy's Enterprise hub.
A prize-winning paper from Oxford's Department of Computer Science describes a cardiac variability model that has been developed into Virtual Assay, a user-friendly software package.