Postdoc: Bond-Centric ML for Chemical Simulations

Danmarks Tekniske Universitet; Ørsted; On-site; DKK 402,000 - 536,000; Full time

Job summary

DTU Chemistry at the Technical University of Denmark (DTU) invites applications for a 2-year postdoctoral position focused on developing machine-learned approaches to interpret chemical simulations and promote bonds as kernels in the interpretation of chemical processes.

The successful candidate will develop novel theory and software, implement methods in optimized codes, and apply them to chemical problems in a collaborative, international environment at DTU in the greater Copenhagen area.

Qualifications

• PhD required or equivalent.
• Strong background in theoretical and computational chemistry or physics.
• Encouraged background in statistics, machine learning, computer science, or mathematics.
• Proven programming skills, especially ML applied within chemical/physical sciences.

Responsibilities

• Engage in theoretical and practical methodological developments.
• Implement methods within optimized computer codes.
• Apply methods to chemical problems through large-scale applications.
• Collaborate within a strong, interdisciplinary team at DTU Chemistry.

Skills

Theoretical Chemistry

Computational Physics

Machine Learning

Programming

Statistics

Education

PhD degree

Tools

Python

C++

Matlab

Job description

DTU Chemistry at the Technical University of Denmark (DTU) invites applications for a 2-year postdoctoral position focused on developing machine-learned approaches to interpret chemical simulations and promote bonds as kernels in the interpretation of chemical processes.

The successful candidate will develop novel theory and software, implement methods in optimized codes, and apply them to chemical problems in a collaborative, international environment at DTU in the greater Copenhagen area.