PhD: Computational Discovery of Advanced Photoactive Molecules

Danmarks Tekniske Universitet; Ørsted; On-site; DKK 320,000 - 420,000; Full time

Job summary

DTU Energy invites applications for a 3-year PhD scholarship in advanced computational chemistry and quantum chemistry designed to discover molecules with unconventional photophysical properties. The project combines state-of-the-art methods and workflows to translate these properties into OLED, photovoltaics, bioimaging and photodynamic therapies.

The successful candidate will develop computational workflows, apply quantum chemistry tools, and employ high-throughput screening, machine learning,

Qualifications

• Master’s degree in theoretical physics, theoretical chemistry, or related fields.
• Experience with computational chemistry, particularly modeling excited state properties.
• Strong background in theoretical quantum chemistry.
• Working knowledge of the Python programming language.
• Experience using HPC platforms.
• Two-year Master’s degree (120 ECTS) or equivalent.

Responsibilities

• Develop computational workflows to design novel molecular structures based on required photophysical properties.
• Use quantum chemistry-based predictive software to capture the desired photophysical properties.
• Search chemical space using high-throughput screening, machine learning and evolutionary algorithms.

Skills

Python

HPC

Theoretical physics

Theoretical chemistry

Computational chemistry

Machine learning

Excited state properties

Education

Master’s degree in theoretical physics/theoretical chemistry

Tools

Python

HPC platforms

Job description

DTU Energy invites applications for a 3-year PhD scholarship in advanced computational chemistry and quantum chemistry designed to discover molecules with unconventional photophysical properties. The project combines state-of-the-art methods and workflows to translate these properties into OLED, photovoltaics, bioimaging and photodynamic therapies.

The successful candidate will develop computational workflows, apply quantum chemistry tools, and employ high-throughput screening, machine learning,