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Machine Learning Engineer


Job details
  • St. Pancras and Somers Town
  • 1 month ago
Applications closed

We have an exciting opportunity available for a Machine Learning Engineer (Data science / Deep learning) to join the Cancer Dynamics Laboratory. The post holder would work across multiple on-going projects of the lab, including a dedicated role within the MANIFEST project (“Multiomic ANalysis of Immunotherapy Features Evidencing Success and Toxicity”), a newly formed ambitious multi-stakeholder consortium involving academic, industry and NHS partners to deliver deep multi-omic profiling for patients with cancer undergoing immunotherapy.

You will join us on a full time, permanent basis, and in return, you will receive a competitive salary starting from £48,600 per annum plus benefits, subject to skills and experience

The Crick’s mission is discovery without boundaries; we don’t limit the direction our research takes. We want to understand more about how living things work to help improve treatment, diagnosis, and prevention of human disease, and generate economic opportunities for the UK. Much of our research is both data- and compute-intensive and relies on advanced Scientific Computing systems, services, and skills.

The Machine Learning Engineer role:

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 of our Machine Learning Engineer:

These include but are not limited to:

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

Provide engineering support and mentoring as required to other members of the project team

To attend, and report research results at regular group meetings.

To write and present work to MANIFEST stakeholders as required.

To engage in relevant MANIFEST programme workflows with academic, NHS and industry partners.

Skills and experience we are looking for in our Machine Learning Engineer??????:

Strong mathematical/statistical background with demonstrable experience in developing deep learning algorithms for research

Expert level technical programming skills, with emphasis on Python (NumPy, PyTorch etc) and preferably experience with R

Experience of applying deep learning techniques to omics datasets

Ability to read machine learning research articles and implement the algorithms described

Experience of working with high performance computing clusters (Bash, Slurm etc)

Good understanding of MLOps for experiment tracking, model and data versioning, hyperparameter tuning and results visualisation

Experience in database technologies: SQL, NoSQL.

An understanding of good software engineering principles

Closing date: 19th January 2025

If you feel you have the skills and experience to become our Machine Learning Engineer, please click ‘apply’ today, we’d love to hear from you!

All offers of employment are subject to successful security screening and continuous eligibility to work in the United Kingdom

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