Machine Learning Engineer (Data science / Deep learning)

We are looking for a data scientist / machine learning engineer to join the project team to work on integrated and multimodal approaches to predicting immune-oncology response for the unique dataset being compiled as part of the MANIFEST consortium. Specifically, this role will be focussed on multiomics (RNASeq, WES, WGS), blood and clinical data initially but there may be opportunity to expand into imaging modalities later on. This is an opportunity to develop state-of-the-art deep learning methods for a remarkable dataset. The post holder will work closely with the Software Engineering and AI team and Cancer Dynamics lab within the Francis Crick Institute. They will also interact closely with other laboratory staff from the MANIFEST platform, as well as with post-docs, students, scientists, technicians from the lab, and scientific partners of MANIFEST. Key Responsibilities

• To develop machine learning based analyses approaches in accordance with the requirements of the project
• Stay current with the latest thinking in the field through building a library of related publications
• Develop approaches to evaluate the performance of ML models in relation to project objectives
• Design and develop high-quality, optimised and maintainable pipelines and software to meet project needs
• Work in close collaboration with clinical scientists, bioinformaticians and other project team members both within the Facility and MANIFEST platform to understand the full range of data and meta-data being produced for the project
• Assist with creating and supporting a productive and efficient standardised model development work-flow as appropriate for the project (including versioning and automation)
• Produce, update or otherwise maintain documentation for project, and present results updates back to the project team and other collaborators
• Assist with workload planning by providing estimates