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- Tasks: Develop machine learning models to enhance molecular sensors using 2D materials.
- Company: University of Warwick's HetSys Centre for Doctoral Training.
- Benefits: Fully funded PhD, tax-free stipend, and research training budget.
- Other info: Join a vibrant community focused on solving global challenges.
- Why this job: Make a real-world impact with cutting-edge technology in a collaborative environment.
- Qualifications: Strong background in physics, engineering, or computer science.
The predicted salary is between 21805 - 21805 £ per year.
About the project
Two-dimensional materials, such as graphene, could be used in molecular sensors - if we can control and tune their properties. You will develop and use top‑of‑the‑line machine learning models to predict the sensor response of these materials under realistic conditions, including in liquids. Combining quantum mechanics and atomic simulation with AI‑driven sampling techniques, you will determine terahertz and Raman spectrograms to directly compare to measurements obtained in the THz labs at Warwick and by our collaborators at the Institute of Saint‑Louis (ISL). By suggesting design modifications to the molecular structures, your work will improve the next generation of molecular sensors.
About HetSys: Harnessing Data, Modelling and Simulation for Real‑World Impact
- Big Questions, Real Impact – From climate modelling and sustainable energy to advanced materials and biomedical systems, HetSys projects apply cutting‑edge computational and mathematical techniques to problems with global significance.
- Interdisciplinary Training – Students gain expertise across physics, engineering, computer science, and applied mathematics, developing versatile skills that open doors to both academia and industry.
- Collaborative Environment – Work alongside leading researchers and industry partners in a supportive, vibrant community that values curiosity, creativity, and collaboration.
- Future‑Focused Careers – HetSys graduates are equipped with highly sought‑after skills in modelling, simulation, and data science, preparing them for impactful careers in research, technology, and beyond.
If you’re excited by the idea of using advanced modelling and simulation to solve complex, real‑world problems, HetSys offers the perfect environment to push boundaries and make a difference.
Awards for UK applicants cover full University fees, give a research training budget and a tax‑free stipend to cover living costs (standard UKRI rate £21,805 in 26/27 – equivalent to national living wage).
PhD Studentship: The Thinnest Sensors: 2D Materials in Liquid Solution in Coventry employer: University of Warwick
Contact Detail:
University of Warwick Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land PhD Studentship: The Thinnest Sensors: 2D Materials in Liquid Solution in Coventry
✨Tip Number 1
Network like a pro! Reach out to current PhD students or alumni from the HetSys programme. They can give you insider info on what it’s really like and might even help you get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a mini-project or presentation that showcases your understanding of 2D materials and machine learning. This will not only impress the supervisors but also demonstrate your passion for the field.
✨Tip Number 3
Be proactive! Don’t just wait for opportunities to come to you. Attend relevant workshops, seminars, or conferences related to materials science and AI. It’s a great way to meet people and learn about potential openings.
✨Tip Number 4
Apply through our website! We’ve got all the latest PhD opportunities listed there. Plus, it’s the best way to ensure your application gets seen by the right people at HetSys.
We think you need these skills to ace PhD Studentship: The Thinnest Sensors: 2D Materials in Liquid Solution in Coventry
Some tips for your application 🫡
Show Your Passion: Let us see your enthusiasm for the project! Talk about why you're excited about working with 2D materials and how you can contribute to the field. A genuine interest can really make your application stand out.
Tailor Your CV: Make sure your CV is tailored to highlight relevant experience and skills that align with the PhD project. Focus on your background in machine learning, quantum mechanics, or any related research you've done. We want to see how you fit into our vision!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell your story. Explain why you’re the perfect fit for this studentship and how your goals align with HetSys. Keep it engaging and personal – we love to get to know our applicants!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the easiest way for us to keep track of your application and ensures you don’t miss any important details. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at University of Warwick
✨Know Your 2D Materials
Make sure you brush up on your knowledge of two-dimensional materials, especially graphene. Understand their properties and potential applications in molecular sensors. This will show your passion for the project and help you engage in meaningful discussions during the interview.
✨Familiarise Yourself with Machine Learning
Since you'll be developing machine learning models, it's crucial to have a solid grasp of relevant algorithms and techniques. Be prepared to discuss how you would apply these methods to predict sensor responses and improve molecular structures.
✨Prepare Questions for Your Supervisor
Dr Peter Brommer is your potential supervisor, so think of insightful questions to ask him about the project and his expectations. This demonstrates your interest and helps you gauge if the PhD programme aligns with your goals.
✨Showcase Your Interdisciplinary Skills
Highlight any experience you have across physics, engineering, computer science, or applied mathematics. The HetSys programme values interdisciplinary training, so be ready to explain how your diverse skill set can contribute to the research and collaborative environment.