Machine Learning Scientist

Join us on our mission to advance science through interdisciplinary innovation, push the boundaries to make a leap in drug discovery and save millions of people’s lives.

About GTN

GTN Ltd is building the world’s most efficient technology for drug discovery: Generative Tensorial Networks. Our technology addresses the main challenges in the search for new drugs with novel technology built on recent interdisciplinary developments in the fields of machine learning and quantum physics, in order to simulate, analyse and search for new chemical compounds. The company is based in central London and run by a passionate and highly skilled team of quantum physicists, machine learning experts, and chemists.

GTN has some of the world’s brightest minds on its advisory board. Their other roles include directing the Max Planck Institute, Professors at Cambridge university, UCL and Ghent university, and Fellow of the Royal Society of Chemistry.

GTN is backed by Tier 1 investors from Europe and US (their other investments include Rigetti Computing and Magic Pony).

About the role

We have four openings for Machine Learning researchers. In addition to familiarity with standard Machine Learning tools such as Tensorflow, the candidates are expected to have experience building and working on large projects. Crucially they need to be strong enough to be able to quickly understand cutting edge Deep Learning research papers and implement related architectures. Experience with generative modes and familiarity with graph convolutional networks is a bonus.

As part of our team, you will be working closely with our CTO, in an intellectually rigorous and fast-paced environment. You will collaborate with both GTN scientists, as well as experts at collaborating institutions such as UCL, Cambridge University, and the Crick, and will be informing the design and performance of the algorithms. You will play a central role in the research and application of novel methods, influence decisions concerning dataset acquisitions, and help GTN identify exciting new problems. As an early employee, you will also participate in general decision making, and help shape the company culture and value.

Requirements

Join us on our mission to advance science through interdisciplinary innovation, push the boundaries to make a leap in drug discovery and save millions of people’s lives.

We encourage innovation and offer budget for publishing and attending conferences. We offer a competitive salary and share in the value that you create through stock options. Compensation package dependent on demonstrated capabilities and experience.

Please email your CV to our team.

Closing date 28 Feb 2018 (starting date flexible, as early as March).