Summary
Join a pioneering research group at DTU Energy, focused on transforming materials discovery from empirical exploration into predictive design. This PhD scholarship aims to advance methodologies in computational chemistry, utilizing machine learning to enhance reaction mechanism discovery through automated simulation methods.
PhD Scholarship in Machine Learning-Accelerated Reaction Mechanism Discovery, DTU Energy, Kgs. Lyngby, Denmark
Designation
PhD Candidate (Machine Learning-Accelerated Reaction Mechanism Discovery)
Table Summary
| Detail | Description |
|---|---|
| Research Area | Computational Chemistry, Machine Learning |
| Location | DTU Energy, Kgs. Lyngby, Denmark |
| Eligibility | Two-year Master’s degree (120 ECTS points) or equivalent |
| Last Date to Apply | April 30, 2026 |
Research Area
- Development of workflows for modeling dynamic multi-phase systems.
- Enhancement of machine learning interatomic potentials.
- Addressing sampling challenges in transition pathways within high-dimensional potential energy surfaces.
Eligibility/Qualification
- Background in computer science, chemistry, physics, materials science, or a related field.
- Experience with deep learning frameworks, particularly in generative models.
- Proficient in atomistic simulations and quantum chemical calculations.
- Interest in software development and automating computational workflows.
- Curiosity about fundamental reaction mechanisms and atomistic processes.
- Willingness to work in an international, interdisciplinary, and collaborative team.
Job Description
As a PhD candidate, you will:
- Develop algorithms addressing the “chicken-and-egg” problem of sampling.
- Contribute to open-source frameworks while systematically guiding explorations towards desired chemical targets.
- Work with domain experts to refine and validate theoretical models with empirical datasets.
How to Apply
Submit a complete online application comprising the following materials as one PDF file:
- A cover letter motivating your application.
- Curriculum vitae.
- Grade transcripts and BSc/MSc diploma, including an official description of the grading scale.
All materials must be submitted in English through the online application form by the deadline.
Last Date to Apply
April 30, 2026 (23:59 Danish time). Applications submitted after this date will not be considered.
