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Postdoc and PhD openings become available on a rolling basis. Informal inquiries via email are welcome.

Start dates and topics are flexible. Topics are in the general areas of:

  • development of nonadiabatic and approximate quantum dynamics methods for condensed phase systems
  • Machine learning of electronic structure
  • Simulation of ultrafast dynamics at surfaces and light-driven catalysis

Specific current opportunities:

Three fully funded 4-year PhD projects in Machine-Learning-Accelerated Simulation of Photocatalysis and Ultrafast Dynamics at Surfaces (flexible 2022-2023 start date)

The project is open to international candidates with a science Bachelor/Master degree (Chemistry, Physics, Mathematics, Computer Science) and covers 4-year stipends including full UK or overseas tuition fees. Successful candidates will become members of the interdisciplinary Computational Surface Science group ( led by Prof. Reinhard Maurer based in the Departments of Physics and Chemistry at the University of Warwick, UK.

The Scientific Mission: Fuel cells, photovoltaic devices, photocatalytic converters – they all are crucial elements in delivering decarbonization and sustainable energy production at a global scale within the coming decades. They all fundamentally involve energy transfer and chemical dynamics at interfaces where molecules, electrons, and light interact to deliver a certain function. The underlying mechanisms of ultrafast dynamics at surfaces triggered by light or electrons are not well understood, which, for example, limits our ability to design photocatalyst materials that deliver optimal light absorption, catalytic activity, and energy transport. Molecular simulation methods and quantum theoretical calculations in principle can address this but have hitherto struggled with tackling such challenging systems. With the emergence of machine learning methods in the physical sciences, this is rapidly changing. The three projects will tackle this ambitious challenge by developing and applying new software tools that combine machine learning methodology, electronic structure theory, and molecular dynamics methodology to simulate ultrafast chemical dynamics at surfaces and in materials.

Training: Successful candidates will join an interdisciplinary research group that provides a collaborative and supportive environment. Projects will often involve teamwork and joint problem-solving between colleagues with complementary skills. All students will be trained in state-of-the-art machine learning methodology, electronic structure theory, and molecular simulation methods. Students will acquire important transferable skills such as software development (Python, Julia) and project management. Substantial resources are available for group members to attend international workshops and conferences. All projects are designed to balance method development and application simulation efforts – the latter will include close collaboration with experimental project partners.

PhD Project: Molecular simulation of plasmonic effects in carbon monoxide reduction chemistry

Several recent ultrafast spectroscopy studies have shown that light-generated hot electrons can selectively activate frustrated rotations in metal-adsorbed carbon monoxide. This can support chemical transformations, for example in the case of CO hydrogenation on ruthenium, which is a bottleneck reaction in syngas and CO2 reforming. In this project, you will use newly developed machine learning surrogate models to simulate the light-driven promotion of CO hydrogenation to CHO on plasmonic catalyst materials. The PhD project will establish the mechanistic details of hot electron interaction with CO and the key design parameters for optimal photocatalytic CO hydrogenation.

Interested candidates should contact Prof. Reinhard Maurer ( with their CV and a motivation statement. Details on the formal application procedure can be found at

Three-year fixed-term PostDoc position as Research Fellow in Computational Chemistry available

We are looking for a postdoctoral researcher to join our efforts on light-driven dynamics at surfaces. In this role, you will work on a curiosity-driven project, towards developing novel machine-learning representations of electronic structure to enable hitherto unfeasible molecular and quantum dynamics simulations. By combining machine-learning methods, nonadiabatic dynamics methods, and Density Functional Theory, the project will develop a first principles-based simulation framework for the description of light and electron-driven reaction dynamics in heterogeneous catalysis and photocatalysis.

The project takes place in a large and vibrant interdisciplinary research group and will provide you with space and resources for your personal career and profile development, combining method development, application to real-world problems, and collaboration with experimental groups. Your project will complement ongoing work by other members in the group working towards common goals. The contract is for a fixed term of up to 36 months.

Who we are: In the Maurer group at Warwick, we aim to develop computational simulation methodology to study quantum phenomena at surfaces with applications ranging from plasmonic catalysis, to nanotechnology, and electrochemistry. Our goal is to combine electronic structure theory, molecular and quantum dynamics methodology, and machine learning methods to achieve an accurate yet computationally feasible description of complex phenomena at solid/gas and solid/liquid interfaces. The currently 15 members of the group come from diverse backgrounds in chemistry, mathematics, and physics, and foster a collaborative and supportive work environment. The group is one of seven computational chemistry groups and part of an interdepartmental computational materials research community spanning the Chemistry, Physics, and Engineering departments.

Who you are: You might have a background in computational chemistry/physics, theoretical condensed matter physics, computer science, or a similar field. You love working on hard problems that live at the boundary of theoretical method and computational software development. You enjoy working in a team where you contribute your expertise and skill set to deliver an ambitious research vision and where you can contribute to the training of PhD and Master’s students. You are excited about opportunities to communicate with international collaborators across disciplinary and cultural boundaries.

Advert coming soon: Please send your CV and motivation statement to

Group Openings

Applications from students interested in research at the Master's, PhD and PostDoc level are always welcome.

Contact us via Email!