Responsibilities;
Developing and applying ML methods from several fields, including, but not limited to, natural language processing, representation learning, and matrix factorisation.
Building applications (APIs or web applications) to democratise the use of pre-trained models to other research scientists
Researching new ML approaches for antibody discovery and patient stratification
Analysing large volumes of high-dimensional data
Working collaboratively with the team, including founders, bioinformatics research groups and external partners
Communicating, interpreting, summarising and visualising data for presentation to different audiences
Keeping up to date on new discoveries, methodologies and approaches that may enhance the companies platform
Requirements:
A PhD (or equivalent experience) in Computer Science, Statistics, Applied Maths, or a Biological Sciences degree with a strong emphasis in ML
Experience with biological data (preferably 'omics data)
Proficiency in Python and PyTorch (or another deep learning framework)
Experience in deploying machine learning models for commercial production and/or large-scale academic projects
A good track record of scientific achievement and publication
A team player who proactively and directly communicates and collaborates with other team members
