Behrouz Arash

OsloMet – Oslo Metropolitan University invites applications for a PhD Fellowship in Deep Learning Models for Designing Solid-State Electrolytes. The position is based in the Department of Mechanical, Electrical and Chemical Engineering at the Faculty of Technology, Art and Design (TKD), located in central Oslo, Norway. This 3-year funded position offers a unique opportunity to contribute to the next generation of battery materials research, focusing on the development and application of deep learning models for molecular dynamics and coarse-grained simulations. The project addresses the safety and performance challenges of current liquid electrolyte-based batteries, which are widely used in portable devices and electric vehicles. Solid-state electrolytes (SSEs) are emerging as safer alternatives, offering improved electrochemical stability and non-flammability, and enabling higher energy densities in Li- and Na-ion batteries. The research aims to design polymer nanocomposite solid electrolytes (PNSEs) by combining hard (ceramic) and soft (polymer) materials, achieving desirable properties such as high ionic conductivity, low interface resistance, enhanced mechanical strength, and superior electrochemical stability. Through advanced molecular simulations and deep learning techniques, the successful candidate will characterize, design, virtually test, and optimize PNSEs for battery applications. The project is highly interdisciplinary, integrating materials science, chemistry, computational modeling, and machine learning. As a PhD Fellow, you will join a creative and inspiring academic community, participate in research groups, and have opportunities for academic development, including potential funding for extended research stays abroad. Eligibility: Applicants must hold a master’s degree in applied mathematics, computational physics, or a related discipline (normally 120 ECTS credits). All master’s exams must be completed by 30 June 2026. Minimum average grade B in master’s subjects and thesis, minimum average grade C in bachelor’s subjects. Written and oral proficiency in English is required. Admission to the PhD programme in Engineering Science at OsloMet is a prerequisite. Experience with advanced simulation techniques, machine learning models for material modeling, proficiency in programming languages (Python, MATLAB, Julia, C++), and molecular dynamics programs (LAMMPS) is advantageous. Knowledge of advanced battery technologies or energy storage systems is desirable. Personal qualities such as independence, collaboration, motivation, analytical skills, and innovation are valued. Funding: The position is fully funded, with a salary of 550,800 NOK per year (2% pension contribution deducted). Additional funding for research stays abroad may be available. Application Process: Apply through OsloMet’s electronic recruitment system by 4 May 2026. Upload all required documents, including application letter, CV, reference letters, certificates/diplomas, transcripts, and proof of foreign education if applicable. Incomplete applications will not be considered. Documents must be in English or a Scandinavian language. OsloMet verifies documents and conducts background checks for relevant positions. Contact: For academic inquiries, contact Head of Research Biplab K Datta ([email protected]) or Associate Professor Behrouz Arash ([email protected]). For administrative questions, contact [email protected]. Join Norway’s third largest university and contribute to cutting-edge battery materials research in a supportive and inclusive environment. The position offers engaging work assignments, participation in research groups, welfare schemes, and a workplace in the heart of Oslo.