At a Glance
- Tasks: Develop cutting-edge AI methods for molecular and protein discovery in a research-focused role.
- Company: Well-funded life science tech company with a focus on innovation.
- Benefits: Competitive salary up to £100,000, hybrid work model, and impactful research opportunities.
- Other info: Collaborative environment with opportunities to shape research direction and impact.
- Why this job: Join a team at the forefront of AI, making a real difference in scientific discovery.
- Qualifications: PhD or equivalent experience in ML, strong publication record, and Python skills required.
A well-funded life science technology company is looking for an exceptional Machine Learning Scientist to develop next-generation AI methods for molecular and protein discovery. This is a research role with real engineering proximity. You will develop novel ML methods for molecules, proteins, and biological systems, working closely with engineers to translate new ideas into practical tools that accelerate scientific discovery. The team values strong scientific contributions and a genuine track record of research impact.
What we are looking for:
- PhD in Machine Learning, Computer Science, Computational Biology, Physics, Mathematics, or a related discipline, or equivalent research experience
- A strong publication record at premier ML conferences such as NeurIPS, ICML, ICLR, AISTATS, or CVPR, or research achievements of comparable quality
- Deep understanding of modern deep learning methods including graph neural networks, transformer architectures, and diffusion models
- Strong Python and PyTorch programming skills
- The ability to independently drive research from idea through to implementation
- Excellent communication and collaboration skills across technical and scientific teams
Particularly strong candidates will also have:
- Experience with 3D machine learning, geometric deep learning, or spatial representations
- Experience working with molecular structures, proteins, drug discovery, or computational chemistry
- Familiarity with molecular generation, protein modelling, docking, or structure prediction
- Experience scaling experiments and collaborating with engineering teams to move research into production
Why this role: You will be working at the frontier of AI for scientific discovery, on problems that matter, alongside a team that takes both the science and the engineering seriously. The role sits at the intersection of original research and practical impact, with real scope to shape the direction of the work.
This role requires existing right to work in the UK. Visa sponsorship is not available. If your background fits, apply below.
Machine Learning Scientist in London employer: Platform Recruitment
As an Electronics Engineer at our Cambridge location, you will be part of a dynamic team that values innovation and collaboration, offering a stimulating work environment where your contributions directly impact high-performance electronic systems. We provide competitive salaries, comprehensive benefits, and ample opportunities for professional growth, ensuring that you can advance your career while enjoying a supportive and inclusive workplace culture.
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We think this is how you could land Machine Learning Scientist in London
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We think you need these skills to ace Machine Learning Scientist in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Platform Recruitment, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Platform Recruitment. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Platform Recruitment
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Platform Recruitment!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
