PhD: ML for Quantum Chemistry of Complex Reactions

Danmarks Tekniske Universitet; Ørsted; On-site; DKK 357,000 - 469,000; Full time

Job summary

DTU, located in Kgs. Lyngby, Denmark, invites applications for a PhD position focused on developing automated and data-driven computational methods for complex chemical reactions.

The project spans quantum chemistry, machine learning, and materials science, with close collaboration to national and international partners. You will contribute to method development, implementation, and application to benchmark systems, while creating curated datasets for classical and quantum-computing studies.

Qualifications

• Background in physics, mathematics, computer science, chemistry, or a related field.
• Experience with quantum chemistry, electronic-structure theory, molecular modelling, or atomistic simulations.
• Interest in machine learning, numerical optimization, or data-driven scientific modelling.
• Programming experience, preferably in Python or a related scientific-computing language.
• Curiosity about chemical bonding, reaction mechanisms, catalysis, or strongly correlated molecular systems.
• Interest in developing computational methods rather than applying existing software.
• Motivation to work in an international, interdisciplinary, and collaborative research environment.

Responsibilities

• Develop computational workflows for describing electronically complex chemical reactions.
• Improve representation of molecular electronic structure across coordinates and states.
• Integrate machine learning to accelerate workflows and identify patterns in molecular data.
• Collaborate in an interdisciplinary environment and contribute to curated datasets.

Skills

Quantum chemistry

Electronic-structure theory

Molecular modelling

Atomistic simulations

Machine learning

Numerical optimization

Data-driven modelling

Python

Computational method development

International collaboration

Education

Two-year master’s degree

Job description

DTU, located in Kgs. Lyngby, Denmark, invites applications for a PhD position focused on developing automated and data-driven computational methods for complex chemical reactions.

The project spans quantum chemistry, machine learning, and materials science, with close collaboration to national and international partners. You will contribute to method development, implementation, and application to benchmark systems, while creating curated datasets for classical and quantum-computing studies.