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- Tasks: Develop and evaluate predictive models linking viral genotype and phenotype data using machine learning.
- Company: Join a large global organisation focused on innovative bioinformatics solutions.
- Benefits: Remote work, competitive contract rates, and potential for extension.
- Why this job: Make a real impact in bioinformatics while working with cutting-edge machine learning techniques.
- Qualifications: Strong background in machine learning, Python proficiency, and experience with biological datasets.
- Other info: Opportunity to work in a dynamic environment with significant research implications.
The predicted salary is between 60000 - 80000 £ per year.
A large global organization are seeking a Senior Machine Learning Scientist to develop and evaluate internal predictive models linking viral genotype and phenotype data based sensitivity analyses. The role focuses on applying established machine‑learning approaches to curated biological datasets to support research, validation, and internal decision‑making. This role will be an initial 6-8 months+ contract with the possibility of extensions. The role can be worked on a remote basis.
Key Skills/Responsibilities:
- Technical Expertise
- Strong background in machine learning or statistical learning with substantial hands‑on experience developing classification models
- Experience working with high‑dimensional, sparse biological or omics datasets
- Strong proficiency in Python for end‑to‑end machine‑learning workflows
- Demonstrated experience designing validation strategies and assessing performance under significant class imbalance and limited sample sizes
- Scientific Rigor
- Clear understanding of model limitations, uncertainty, and overfitting risks in real‑world biological datasets
- Experience delivering machine‑learning analyses intended to inform research and internal decision‑making
- Experience making principled methodological recommendations in the face of incomplete or noisy data
- Preferred Qualifications
- Experience working with biological sequence data or genotype–phenotype analyses
- Experience with interpretability or explainability approaches applied to biological machine‑learning models
- Background in pharmaceutical, biotech, or regulated research environments
- Machine Learning Model Development
- Develop classification models to analyze curated genotype–phenotype datasets
- Apply appropriate modeling strategies to predict viral sensitivity or resistance based on sequence‑derived features
- Implement training, validation, and hyperparameter‑tuning workflows using predefined datasets
- Evaluate alternative feature representations provided by the bioinformatics team and assess their suitability
- Model Evaluation and Robustness
- Assess model performance using metrics appropriate for imbalanced biological datasets
- Evaluate robustness across data splits, phenotype definitions, and successive data releases
- Identify failure modes, instability, and limitations, and document their implications
- Document modeling assumptions, trade‑offs, uncertainty, and limitations in a reproducible and transparent manner
- Interpretability and Insight Generation
- Provide interpretable summaries of model behavior, including feature importance and consistency of signals
- Identify amino‑acid positions or features that recur across models or resampling strategies, while highlighting where signals are not reproducible
- Clearly document and communicate findings, assumptions, and caveats within the bioinformatics team
Senior Machine Learning Scientist – Bioinformatics, Python, ML – UK, Remote in Liverpool employer: MRP-Global
Contact Detail:
MRP-Global Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Scientist – Bioinformatics, Python, ML – UK, Remote in Liverpool
✨Tip Number 1
Network like a pro! Reach out to folks in your field on LinkedIn or at industry events. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to bioinformatics. We want to see your Python prowess and how you tackle real-world problems, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and be ready to discuss your past experiences with high-dimensional datasets. We recommend practising with mock interviews to boost your confidence and refine your answers.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior Machine Learning Scientist – Bioinformatics, Python, ML – UK, Remote in Liverpool
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your technical expertise in machine learning and Python. We want to see your hands-on experience with classification models and how you've tackled high-dimensional biological datasets. Don’t hold back on showcasing your achievements!
Be Clear and Concise: When writing your application, clarity is key! We appreciate straightforward language that gets to the point. Avoid jargon unless it’s necessary, and make sure your passion for bioinformatics shines through.
Tailor Your Application: Take a moment to customise your application for this role. We’re looking for specific experiences related to model evaluation and robustness in biological datasets. Show us how your background aligns with what we need!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at MRP-Global
✨Know Your Models Inside Out
Make sure you can discuss your experience with classification models in detail. Be prepared to explain how you've developed and validated these models, especially in the context of high-dimensional biological datasets. This will show that you not only understand the theory but also have practical experience.
✨Showcase Your Python Skills
Since proficiency in Python is crucial for this role, be ready to talk about specific projects where you've used Python for machine learning workflows. Highlight any libraries or frameworks you’re familiar with, and consider bringing along code snippets or examples to demonstrate your expertise.
✨Discuss Scientific Rigor
Be prepared to discuss how you handle model limitations and uncertainty, particularly in biological datasets. Share examples of how you've documented assumptions and trade-offs in your previous work, as this will illustrate your commitment to scientific integrity and transparency.
✨Prepare for Interpretability Questions
Given the focus on interpretability in this role, think about how you've communicated model behaviour and findings in the past. Be ready to explain your approach to feature importance and how you've dealt with noisy data, as this will demonstrate your ability to provide actionable insights from complex models.