Research Scientist

About the role

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Research Scientist in Science

Founded in 2014, InstaDeep is today an EMEA leader in decision-making AI products for the Enterprise, with headquarters in London, and offices in Paris, Berlin, Tunis, Lagos, Dubai, Cape Town and the USA. InstaDeep has been named among the Top 100 global AI startups for three consecutive years by CB Insights, as well as one of the 100 most promising B2B companies in Europe, by Sifted. We have created an environment that ensures a challenge by working closely with a broad spectrum of high-quality clients, pushing you to thrive in an environment that’s rarely tedious and always looking to push you to come up with outside-the-box solutions using cutting-edge technologies. In our mission to stay ahead of the curve, we are proud to partner with firms such as BioNTech SE, Google DeepMind, NVIDIA and Intel, and world-class universities such as MIT, Oxford, UCL, and Imperial College London. We are also an NVIDIA Elite Service Delivery Partner and Google Cloud Partner.

Are you a Research Scientist in Science? You will contribute to knowledge in different fields, and plan and conduct experiments to help expand the canon of the company's scientific knowledge.

If so then keep reading….

As a Research Scientist in Science, you’ll be a part of the Research department,

The Research Scientist in Science must accomplish the following:

- Collaborate with other researchers and experts to develop machine-learning methods for problems in computational biology.

- Engage and assist in the identification of research directions

- Contribute to the design and implementation of models, tools and libraries to accelerate our research effort.

- Adapt neural network algorithms to deploy on supercomputing architectures to best exploit modern parallel environments

- Report and present experimental results and research findings clearly and effectively, both internally and externally, verbally and in writing.

- Contribute to the team’s publication efforts.

- Bridge the gap between the research and product teams by integrating new fundamental research into applied projects.

Requirements:

- Ph.D. degree in Computer Science, Machine Learning or a related field.

- Experience using Deep Learning frameworks such as PyTorch, Tensorflow and/or Jax.

- Experience in developing and debugging in Python3 or similar languages.

- Experience with high-performance computing methods and frameworks such as MPI, Ray (distribution on clusters of CPUs and accelerators)

- Experience in planning and conducting research works