PhD scholarship in Machine Learning for Quantum Chemistry of Complex Reactions - DTU Energy

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

Join a research environment focused on developing next-generation computational methods for molecular systems where standard electronic-structure approaches reach their limits. Many chemically important reactions, including catalytic and bioinorganic processes, involve electronic structures that change qualitatively along the reaction path. Describing such systems reliably is a major challenge for both classical quantum chemistry and future quantum-computing applications.

This PhD project will contribute to the development of automated and data-driven approaches for building more robust computational descriptions of complex chemical reactions. The project combines ideas from quantum chemistry, machine learning, numerical optimization, and molecular modelling. The long-term goal is to enable reliable reaction-path datasets and reference calculations for systems with strong electronic complexity, including cases relevant to catalysis, energy conversion, and quantum-computing benchmarks.

You will be part of an interdisciplinary research environment connected to quantum technologies and computational materials chemistry. You will be tightly integrated into the Novo Nordisk Foundation Quantum Computing Programme (NQCP) and collaborate with colleagues from Copenhagen University regularly, especially within the Algorithms & Applications team of NQCP, and with colleagues for the Pioneer Center on Accelerated P2X Materials Discovery (CAPeX) at DTU Energy

Responsibilities and qualifications

As a PhD candidate, you will develop computational workflows for describing electronically complex chemical reactions. Your work will focus on improving how molecular electronic structure is represented consistently across reaction coordinates, chemical environments, and electronic states. This includes developing automated strategies for identifying the most relevant electronic degrees of freedom, validating them against high-level calculations, and using machine learning to accelerate parts of the workflow.

The project will involve method development, implementation, and application to molecular benchmark systems. You will work with quantum-chemical calculations, data-driven models, and automated workflows, and you will contribute to generating curated datasets that can support both classical electronic-structure method development and future quantum-computing studies.

What to expect

• Develop new computational approaches for challenging molecular reactions where conventional electronic-structure methods are difficult to apply reliably.
• Work at the interface of quantum chemistry, machine learning, and quantum technologies.
• Build automated workflows for analysing chemical reaction paths and comparing electronic structures across changing molecular geometries.
• Use machine learning to accelerate expensive parts of electronic-structure analysis and identify relevant patterns in molecular data.
• Collaborate in an interdisciplinary research environment involving computational chemistry, materials modelling, and quantum technologies.
• Contribute to software tools, reproducible workflows, and open scientific datasets.

You ideally have

• A 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.

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

Approval and Enrolment

The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

Assessment

The assessment of the applicants will be made by Assistant Professor Miguel Steiner, Professor Tejs Vegge and Professor Gemma Solomon.

We offer

DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms

The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

Starting date is 1 December 2026 (or according to mutual agreement, but no later than January 2027). The position is a full-time position.

You can read more about career paths at DTU here.

Further information

Further information may be obtained from Miguel Steiner ([e-mail])

You can read more about NQCPat www.nqcp.ku.dk

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar "PhD relocation to Denmark and startup "Zoom" seminar" for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.

At the Pioneer Center CAPeX and the Department of Energy Conversion and Storage (DTU Energy), we focus on the development of simulational and machine learning techniques for accelerated materials discovery, and research and development of advanced materials, components and systems, as well as on their applications as sustainable energy technologies. This position is further integrated into the Novo Nordisk Foundation Quantum Computing Programme. The programme’s mission is to enable the development of fault tolerant quantum computing (FTQC) hardware and quantum algorithms that solve life-science relevant chemical and biological problems.

DTU – For the benefit of society since 1829 Through research and education at an international top level, we create solutions to the major societal challenges of our time and help secure Europe's global leadership in sustainable technological development. Since Hans Christian Ørsted founded DTU almost 200 years ago, our mission has remained the same: We develop and create value through the natural and technical sciences for the benefit of society. DTU has 13,800 students, 1,600 PhD students, and 6,500 employees. We work in an international environment and have an inclusive, stimulating, and informal work culture. DTU has campuses in all parts of Denmark and in Greenland and collaborates with the best universities around the world.

Location

Kgs. Lyngby, Denmark

Apply Before

2026-09-15T21:59:00+00:00