PhD Candidate in Advancing Corrosion Science Through AI and High-Throughput Experimentation
Join a new research group at NTNU to revolutionize corrosion science using AI-driven data extraction and high-throughput electrochemical experimentation.
Best for:Best for candidates with a background in engineering or materials science who are eager to bridge the gap between AI-driven data analysis and experimental electrochemistry.
Overview
The Department of Mechanical and Industrial Engineering at NTNU is seeking a motivated PhD candidate to join a newly formed research group focused on corrosion and corrosion protection. This project aims to modernize corrosion research by transitioning from traditional case-specific studies to a data-driven approach using AI and high-throughput experimentation. The successful candidate will develop methods to extract corrosion data from scientific literature using natural language processing and design electrochemical setups for rapid screening. The research will specifically target alloys relevant to carbon capture and storage applications. This position offers an opportunity to contribute to a growing team while pursuing a doctoral degree in a supportive, international environment.
What you'll do
- Complete doctoral education and obtain a PhD degree.
- Conduct high-quality research within the project framework of AI-driven corrosion analysis.
- Publish research findings in academic journals and disseminate results to the public.
- Actively participate in the Corrosion and Corrosion Protection research group.
- Engage in international academic activities, including conferences and workshops.
Requirements
Degree required: Master's degree in mechanical and industrial engineering, chemical engineering, chemistry, or materials science.
Degree offered: PhD
Language: English; high proficiency required for research and dissemination.
Instruction: English
- Strong academic background with a grade average of B or better on the NTNU scale.
- Completion of a major independent research project (minimum 30 ECTS) equivalent to a master's thesis.
- Demonstrated interest in materials science, electrochemistry, or AI applications in engineering.
- Proficiency in oral and written English.
- Must meet the admission requirements for the faculty's Doctoral Programme.
- Must be able to be physically present at the institution on a daily basis.
- Must pass export control assessments regarding the transfer of knowledge and technology.
Funding & terms
How to apply
Deadline: 2025-03-01
Applications must be submitted electronically via the Jobbnorge portal. Ensure all required documents are in English and clearly demonstrate how your background meets the selection criteria.
- CV
- Bachelor's and Master's transcripts and diplomas
- Master's thesis or draft
- Project outline (max 1500 words)
- Letter of motivation (max 400 words)
- List of publications
- Contact information for three referees
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