Research Scientist (Drug discovery and machine learning)

Location: London (Flexible)

Salary: competitive

Position type: full-time

Start date: immediate

Candidates welcomed: all genders, nationalities, backgrounds and orientations

Rahko is a quantum machine learning company focusing on quantum and quantum-inspired algorithms for drug discovery and development.

We are a small and fast-growing startup with huge ambitions and a strong international profile. We work with several of the world's most innovative pharmaceutical, drug discovery and quantum computing companies, and are advised by several world-leading scientists. Read more about Rahko's work and team here .

Rahko brings together classical computational methods, more recent machine/deep learning methods and quantum computing to improve the speed and accuracy of quantum chemistry simulations for drug discovery and development.

As a valued member of our team, you will work closely with our expert quantum machine learning and computational chemistry scientists to develop state-of-the-art in silico methods for drug discovery and development.

You will have a PhD (or equivalent industry experience) in medicinal chemistry, computational chemistry, computational biology, machine learning or a related discipline.

You will need:

1. Background in computer aided drug design (ideally in an industrial setting)
2. Background in machine learning

Ideally, you will also have:

1. Experience in molecular simulation, cheminformatics or bioinformatics
2. Experience with advanced machine learning methods (generative modelling, graph neural networks)

Not sure if you meet the requirements? We recognise that great candidates come from different backgrounds, and we would love to hear from you even if you don't think you exactly meet the above requirements.

Rahko is an inclusive employer that celebrates diversity and welcomes candidates of all backgrounds, genders and orientations.

Due to an expected high volume of applications, we will only be able to contact candidates who have been selected to progress. We appreciate your understanding and thank you for your interest in joining our team.