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Raffaela Cabriolu

3 months ago

PhD Candidate in AI-Driven Computational Modeling of Catalytic Mechanism Norwegian University of Science and Technology in Norway

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available

Deadline

December 31, 2026
Country flag

Country

Norway

University

Norwegian Institute of Science and Technology

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Where to contact

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Keywords

Computer Science
Chemistry
Materials Science
Surface Science
Molecular Dynamics
Condensed Matter Physics
Monte Carlo Simulation
Density Functional Theory
Matter Theory
Physics
Interatomic Potential
Machine learning

About this position

The Department of Physics at the Norwegian University of Science and Technology (NTNU) in Trondheim, Norway, invites applications for a PhD position in the Materials Theory group, focusing on AI-driven computational modeling of catalytic mechanisms. This opportunity is part of the DYNCAT project, funded by the Research Council of Norway (NFR), which aims to develop highly predictive, physics-based, and AI-enhanced computational models to study and optimize the Rochow-Müller process—the industrial method for producing raw materials for silicone production.

The project centers on improving production efficiency and control through advanced particle-based simulation techniques and data-driven modeling approaches. A particular emphasis is placed on understanding the catalytic mechanisms and the formation of dichlorodimethylsilane (M2), the key product of the Rochow-Müller reaction. The successful candidate will join an international research environment and contribute to the computational modeling efforts within the Materials Theory Group, collaborating closely with research scientists at SINTEF Industry, who bring expertise in experimental and theoretical catalysis, surface science, and adsorption processes.

Key duties include developing and applying artificial intelligence (AI) and machine learning (ML) methods for modeling catalytic mechanisms relevant to silicon formation, creating AI/ML-driven computational workflows that leverage atomistic and electronic structure simulation data (such as Molecular Dynamics, Monte Carlo, and Density Functional Theory), and integrating these models with particle-based simulations for predictive, multiscale descriptions of catalytic processes. The candidate will benchmark and validate AI/ML predictions against DFT- and MD/MC-based results and experimental trends, perform high-performance computing simulations, and actively participate in interdisciplinary research discussions. Presentation of research findings at international conferences and publication in peer-reviewed journals are expected.

Applicants must hold a relevant academic background in physics, computational chemistry, or engineering, with documented experience or formal training in AI/ML methods. A strong academic record (average grade B or better in a Master's degree or equivalent) is required, and candidates must meet the requirements for admission to NTNU's Doctoral Programme. Fluency in spoken and written English is mandatory, with additional documentation required for applicants from non-English-speaking countries outside Europe. Preferred qualifications include experience in computational science, physics, materials science, or related fields, strong programming skills (C/C++, Python, Julia), familiarity with atomistic simulation methods, and motivation for AI-driven modeling of physical and chemical processes.

The position is supervised by Associate Professor Raffaela Cabriolu (NTNU) and Dr. Francesca L. Bleken (SINTEF Industry). The employment period is three years, with a gross annual salary of NOK 550,800 and a 2% statutory contribution to the State Pension Fund. The successful candidate must gain admission to the PhD programme in physics within three months of starting the contract and participate in an organized doctoral programme throughout the employment period. NTNU offers a supportive, diverse, and inclusive working environment, career guidance, and favorable terms as a member of the Norwegian Public Service Pension Fund.

Applications must be submitted electronically via Jobbnorge.no by 9th January 2026. Required documents include transcripts and diplomas for Bachelor's and Master's degrees, CV, copy or draft of Master's thesis, documentation of completed Master's degree, a short motivation letter, and names/contact information of three referees. All documents must be in English. For questions about the position, contact Associate Professor Raffaela Cabriolu at [email protected].

Trondheim offers a vibrant cultural scene, excellent welfare services, and a high quality of life, making it an attractive location for international researchers. NTNU is committed to diversity and encourages applications from candidates of all backgrounds.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

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