Summer Internship in Quantitative & Machine Learning Research

Quantitative Research London, United Kingdom


Description

G-Research is a leading quantitative research and technology company. We use scientific techniques, big data and world-class technology to predict future movements in financial markets, and develop the platform to deploy these ideas globally. We offer a dynamic, flexible and highly stimulating environment where good ideas are prized and rewarded.

G-Research is looking for exceptional PhD students to enrol in our 2017 Summer Research Programme. This 10 week programme is challenging, but rewarding, and will give you an invaluable insight into what it means to be a Machine Learning Researcher. Working alongside our experienced Researchers, the programme will task you with solving tough problems with real data, and give you exposure to some of the brightest minds in the industry.

The Role

For the duration of the programme, you will be paired with one of our Machine Learning Researchers who will act as a mentor as you work on projects. Our aim is to accurately reflect what a full time role as a Machine Learning Researcher would look like day-to-day, and enable you to experience the analytical methods we use to carry out research.

Over the course of the Summer Internship you will receive structured feedback and reviews to enable you to improve and develop, culminating in a final presentation to senior management of your research ideas. We are a very social firm, and you will have a full itinerary of social and networking events with peers throughout the Programme. Upon successful completion of the programme, you may be offered the opportunity to join us full-time once you have completed your PhD.

We offer a highly competitive salary for the duration of the programme, and working hours of 9-6pm

The Individual

-You will have an extremely strong background in mathematics, machine learning and/or computer science.

-You should have been involved in the implementation of at least one of a machine learning model.

-You will have an interest in applying mathematical concepts to real world financial problems & in implementing theoretical insights as working code.

-You will also be able ability to work independently in a research environment.

-Numerical programming is an integral part of the role: experience in an object oriented language is very desirable.

-Participation in post-graduate degree programme in machine learning is also desirable, as is a demonstrable interest in finance.