PhD Candidate: AI-Driven Materials Data & Reasoning via LLMs

Arbeidsplassen; Trondheim; On-site; NOK 520,000 - 560,000; Full time

Benefits offered by this job

Mentor programme

Inclusive environment

Norwegian language training

Job summary

NTNU invites applications for a PhD candidate position in machine learning for materials science. The project focuses on developing LLM-assisted methods to extract and organize complex materials data, with emphasis on phase diagrams and oxides.

You will be employed by NTNU, with co-supervisors from Norsk Regnesentral, and spend extended research stays. The role offers an internationally oriented research environment, close collaboration with leading researchers, and a structured PhD programme

Qualifications

• Master's degree in materials science, solid-state chemistry, condensed matter physics, or closely related discipline.
• Strong academic record with average grade equal to B or better on NTNU scale.
• Documented experience with Python or other relevant programming language.
• Good oral and written presentation skills in English.

Responsibilities

• Perform high-quality research within the scope of the project.
• Complete the PhD education and training programme.
• Publish results in internationally recognised journals and conferences.
• Actively participate in and develop collaboration with NTNU and Norsk Regnesentral.
• Contribute to a constructive and inclusive research environment.

Skills

Python

English proficiency

Education

Master's degree in materials science or related field

Job description

NTNU invites applications for a PhD candidate position in machine learning for materials science. The project focuses on developing LLM-assisted methods to extract and organize complex materials data, with emphasis on phase diagrams and oxides.

You will be employed by NTNU, with co-supervisors from Norsk Regnesentral, and spend extended research stays. The role offers an internationally oriented research environment, close collaboration with leading researchers, and a structured PhD programme