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Postdoctoral Scientist (Machine Learning)
Job summary
A leading technology company is offering a full-time Postdoctoral Scientist position to apply machine learning in plasma science. You'll design algorithms to predict properties and improve modeling efficiency. The role requires a PhD and knowledge of Python and machine learning frameworks like TensorFlow. Hybrid working is offered, with a salary range of £35,000 to £45,000.
Qualifications
- A PhD in a related field is required.
- Experience with machine learning in scientific domains is essential.
- Strong publication record in peer-reviewed journals is necessary.
Responsibilities
- Design and implement ML models for plasma simulation.
- Develop algorithms to enhance plasma modeling workflows.
- Collaborate with scientists to integrate ML predictions.
Skills
Education
Tools
Get AI-powered advice on this job and more exclusive features.
Join Quantemol to advance the frontiers of plasma science through the application of machine learning. You will design and implement algorithms to predict physical and chemical properties, and develop methods to expedite simulation times in plasma modelling. Working closely with scientists and software developers, your work will drive innovative computational tools and high-impact research. This is a full-time position based in London (hybrid working model with around 2-4 office days per month), with a salary range of £35,000 to £45,000.
- Design and implement machine learning models for property prediction and plasma simulation.
- Develop algorithms to accelerate complex plasma modelling workflows.
- Collaborate with scientists to integrate ML-driven predictions into Quantemol’s software platforms.
- Present findings at international conferences, workshops and to clients; publish research outcomes in peer-reviewed journals.
- Contribute to project planning, reporting, and achievement of research milestones.
- Participate in consultancy projects involving machine learning applications to plasma science.
- Work closely with software developers to deploy robust and efficient ML pipelines.
- Contribute to a collaborative, interdisciplinary research environment.
Required
- A PhD in Chemistry, Physics, Computer Science, Applied Mathematics, or a closely related discipline.
- Proven research experience in machine learning applied to scientific domains.
- Strong record of publications in peer-reviewed journals or impactful technical reports.
- Proficiency in Python and experience with ML frameworks (e.g. TensorFlow, PyTorch, scikit-learn).
- Strong analytical and problem-solving abilities.
- Excellent communication and collaboration skills.
Preferred
- Experience applying machine learning to computational physics, chemistry, or materials science.
- Familiarity with plasma modelling or electron-molecule interaction data.
- Experience with high-performance computing environments.
- Knowledge of version control systems (e.g. Git).
- Understanding of software development methodologies (e.g. Agile).
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.