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- Tasks: Join our team to develop cutting-edge machine learning methods for predicting immune-oncology responses.
- Company: The Francis Crick Institute is a leading biomedical research facility in London focused on health and disease.
- Benefits: Collaborate with top scientists, access state-of-the-art resources, and contribute to impactful research.
- Why this job: Be part of groundbreaking research that translates discoveries into real-world treatments for serious diseases.
- Qualifications: Experience in data science or machine learning; familiarity with multiomics and clinical data is a plus.
- Other info: Opportunity to work in a collaborative environment with diverse teams and cutting-edge technology.
The predicted salary is between 43200 - 72000 £ per year.
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 workflow 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
About us
The Francis Crick Institute is a biomedical discovery institute dedicated to understanding the fundamental biology underlying health and disease. Its work is helping to understand why disease develops and to translate discoveries into new ways to prevent, diagnose and treat illnesses such as cancer, heart disease, stroke, infections, and neurodegenerative diseases.
An independent organisation, its founding partners are the Medical Research Council, Cancer Research UK, Wellcome, UCL, Imperial College London and King’s College London.
The Crick was formed in 2015, and in 2016 it moved into a new state-of-the-art building in central London which brings together 1500 scientists and support staff working collaboratively across disciplines, making it the biggest biomedical research facility under in one building in Europe.
The Francis Crick Institute will be world-class with a strong national role. Its distinctive vision for excellence includes commitments to collaboration; developing emerging talent and exporting it the rest of the UK; public engagement; and helping turn discoveries into treatments as quickly as possible to improve lives and strengthen the economy.
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Machine Learning Engineer (Data science / Deep learning) employer: The Francis Crick Institute
Contact Detail:
The Francis Crick Institute Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (Data science / Deep learning)
✨Tip Number 1
Familiarize yourself with the latest advancements in multiomics and deep learning. This will not only help you understand the project better but also demonstrate your commitment to staying current in the field during discussions with the team.
✨Tip Number 2
Engage with the scientific community by attending relevant conferences or webinars. Networking with professionals in the field can provide insights into the latest research and may even lead to valuable connections within the MANIFEST consortium.
✨Tip Number 3
Prepare to discuss your experience with machine learning pipelines and model evaluation techniques. Being able to articulate your approach to developing optimized and maintainable software will set you apart from other candidates.
✨Tip Number 4
Show enthusiasm for collaboration by highlighting any past experiences working in interdisciplinary teams. The role requires close interaction with various specialists, so demonstrating your ability to work well with others is crucial.
We think you need these skills to ace Machine Learning Engineer (Data science / Deep learning)
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the key responsibilities. Highlight your experience with multiomics, machine learning, and collaboration with clinical scientists in your application.
Tailor Your CV: Customize your CV to reflect relevant skills and experiences that align with the requirements of the Machine Learning Engineer position. Emphasize your expertise in deep learning methods and any previous work with biomedical data.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for biomedical research and your understanding of the project goals. Mention specific projects or experiences that demonstrate your ability to develop machine learning analyses and collaborate effectively.
Showcase Continuous Learning: In your application, mention any recent publications, courses, or workshops you have attended related to machine learning and data science. This shows your commitment to staying current in the field and your readiness to contribute to the team.
How to prepare for a job interview at The Francis Crick Institute
✨Understand the Project's Focus
Make sure you have a solid grasp of the MANIFEST consortium's goals, especially regarding immune-oncology response and multiomics data. Familiarize yourself with RNASeq, WES, and WGS techniques, as well as how they relate to clinical data.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning algorithms and deep learning methods. Highlight any relevant projects where you've developed or optimized ML models, particularly in biomedical contexts.
✨Emphasize Collaboration
Since this role involves working closely with various teams, demonstrate your ability to collaborate effectively. Share examples of past experiences where you successfully worked with scientists, bioinformaticians, or other stakeholders.
✨Stay Current with Research
Express your commitment to staying updated on the latest developments in machine learning and biomedical research. Mention any relevant publications or conferences you've engaged with, showing that you're proactive about your professional growth.
