PhD in Computational Molecular Design

Technical University of Denmark; Kongens Lyngby; On-site; DKK 357,000 - 402,000; Full time

Job summary

Technical University of Denmark (DTU) invites applications for a PhD position in an interdisciplinary project at the Center of Energy Resources Engineering, DTU Chemical Engineering. You will develop and validate coarse-grained molecular models and implement multi-scale simulation methods for polymers, MOFs, and advanced materials for sustainable technologies.

The role combines experimental and computational collaboration across DTU Chemical Engineering and DTU Energy, requiring strong

Qualifications

• Strong fundamentals in Chemical Engineering, Materials Science or closely related discipline.
• Two-year master's degree required.
• Fluent written and spoken English.

Responsibilities

• Development and validation of new molecular models at the atomistic or coarse-grained level.
• Development of new and extension of existing simulation methodologies to improve efficiency and accuracy.
• Use of computational methods to study properties of advanced materials.
• Dissemination of research through peer-reviewed publications and conferences.
• Completion of PhD coursework and teaching assistant activities as part of the DTU PhD program.
• Supervision of BSc and MSc student projects.

Skills

Strong programming skills

Molecular thermodynamics

Molecular simulation

Physics-inspired machine learning

Education

Master's degree (2-year) or equivalent

Tools

GROMACS

LAMMPS

RASPA

Job description

If you are interested about establishing your career in an interdisciplinary area related to chemical engineering, novel materials design and advanced computational methods and you are looking for the best possible foundation for fulfilling your dreams and ambitions, then you should consider this opportunity. We invite you to apply for a PhD position on a newly established project at the Center of Energy Resources Engineering, DTU Chemical Engineering. You will be involved in the development, parameterization and validation of new coarse-grained molecular models and the development and implementation of systematic molecular simulation methods for novel polymers, metal-organic frameworks (MOFs) and other advanced complex materials and composites that are promising for industrial sustainable technologies. Molecular simulation output will be used for the training of machine learning models and prediction of properties for materials not synthesized in the lab, yet. In parallel, you will be part of a project that brings together experimental and computational research groups from DTU Chemical Engineering and DTU Energy.

Responsibilities and qualifications

Your overall focus will be to contribute to the development of a powerful computational platform based on multi-scale methodologies for the design of novel materials to be used for various sustainable energy technologies, such as CO2 capture, H2 storage and others. You will work with other PhD students and post-docs with similar expertise and passion for Molecular Thermodynamics, Molecular Simulation, and/or Machine Learning. You will collaborate with researchers from other groups involved in the project.

A successful candidate for this position should have strong knowledge of the fundamentals in Chemical Engineering, Materials Science or closely related discipline.

Your responsibilities will include:

• Development and validation of new molecular models at the atomistic or coarse-grained level,
• Development of new, and implementation and extension of existing simulation methodologies aiming to improve efficiency and accuracy,
• Use of these computational methods to study properties of various advanced materials,
• Dissemination of research achievements through peer-reviewed publications in top rated journals and highly prestigious international conferences,
• Successfully completion of PhD courses and pursue of teaching assistant work as part of the DTU PhD program,
• Supervision of BSc and MSc student projects.

We are looking for highly motivated and academically strong candidates who have:

• Strong programming skills,
• Proven research experience in molecular thermodynamics, molecular simulation and/or physics inspired-machine learning,
• Hands-on experience with one of the widely used molecular simulation platforms such as GROMACS, LAMMPS, RASPA, or similar,
• Ability to work and think independently while contributing to successful completion of collaborative research projects,
• Good written and oral communication skills in English.

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