Dr. Nabil Khossossi

Computational Materials Scientist & AI Researcher

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Researcher at DIFFER

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Guest Researcher at TU Delft

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Based in Netherlands

Bridging Quantum chemistry, Materials Science, and Artificial Intelligence

I am a computational materials scientist exploring how electrons, atoms, and algorithms can jointly design the next generation of sustainable materials. My research bridges quantum simulations with artificial intelligence to build autonomous discovery pipelines for catalysts and energy materials. I believe that the future of materials science lies in connecting first-principles accuracy with machine learning speed, where computation becomes not just a tool, but a creative partner in discovery.

50+

Publications

h-index

1370+

Citations

About My Journey Publications

About Me

The intersection of curiosity, computation, and global collaboration

My journey began in Morocco with a fascination for the mathematical beauty underlying physical phenomena. This curiosity led me through the halls of Mohammed V University, where I delved deep into the mathematical foundations of density functional theory, and later to the prestigious summer schools at ICTP Trieste, where I was exposed to cutting-edge computational methods that would shape my career.

I believe that computational approaches, when properly integrated with experimental validation, can dramatically accelerate the discovery and optimization of materials for clean energy technologies.

The transformative opportunity came through an Africa-Sweden Research Cooperation grant, enabling collaborative doctoral research between Moulay Ismail University and Uppsala University. This international experience taught me that the most innovative solutions emerge at the intersection of diverse perspectives and methodologies. Working under the guidance of Prof. Abdelmajid Ainane and Prof. Rajeev Ahuja, I developed computational approaches that bridge multiple scales—from quantum mechanical insights to practical materials design.

Today, my work at DIFFER's AI4Mat initiative and as a Guest Researcher at TU Delft represents the culmination of this journey. I'm not just applying established methods—I'm developing new computational frameworks that integrate physics-based simulations with artificial intelligence, creating autonomous discovery pipelines that can identify materials with unprecedented precision and speed.

What drives me is the conviction that materials science holds the key to addressing global energy challenges. Every algorithm I develop, every simulation I run, and every collaboration I foster is guided by the vision of a sustainable energy future powered by intelligently designed materials.

💼 Open to

Academic Journey

From mathematical foundations to cutting-edge AI applications

My academic path has been shaped by international collaborations, prestigious fellowships, and a commitment to pushing the boundaries of computational materials science.

2024 - Present

Researcher - AI4Mat Initiative

Dutch Institute for Fundamental Energy Research (DIFFER)

Working on the development of autonomous materials discovery frameworks within the Artificial Intelligence for Materials Discovery (AI4Mat) initiative. Pioneering the integration of quantum mechanical simulations with machine learning for accelerated catalyst design.

2022 - 2024

Postdoctoral Researcher

Delft University of Technology (TU Delft)

Machine learning-based computational design of efficient and low-cost catalysts for Hydrogen Evolution Reaction. My research combines density functional theory (DFT) with AI to accelerate the discovery of novel materials. By training models on large chemical datasets, I identify promising candidates for hydrogen production—making the process faster, scalable, and data-driven.

2021 - 2022

J. Gustaf Richert Postdoctoral Fellow

Uppsala University, Materials Theory Group

Fellowship focusing on computational studies of sustainable energy materials using ultra-thin nanomaterials. Developed advanced computational methods for predicting electronic, electrochemistry, and transport properties with applications in hydrogen storage and battery technologies.

2017 - 2021

Doctoral Research

Moulay Ismail University & Uppsala University

Collaborative PhD through Africa-Sweden Research Cooperation grant. Dissertation: "Materials Modelling for Energy Harvesting: From Conversion to Application Through Storage" - establishing novel computational approaches for optimizing materials across the entire energy cycle.

2015 - 2017

Master's in Mathematical Physics

Mohammed V University, Rabat

Focused on advanced mathematical methods for quantum and statistical physics, with applications in electronic structure theory and condensed matter systems. Developed a solid foundation in functional analysis, group theory, and partial differential equations, essential for modeling quantum many-body interactions and understanding the theoretical underpinnings of density functional theory (DFT).

Research Philosophy

The principles that guide my scientific approach

My research philosophy centers on the belief that the most impactful scientific discoveries emerge at the intersection of disciplines. By combining the rigor of quantum mechanics with the adaptability of machine learning, we can overcome the traditional limitations of computational materials science and enable more rapid discovery of materials with tailored properties.

"I am committed to fostering collaborative environments that bring together computational and experimental expertise, strengthening the impact of theoretical predictions through validation and refinement, ultimately accelerating the transition from computational models to practical applications."

This approach has guided me from my early work on pure theoretical investigations to my current focus on applied computational approaches that directly address real-world energy challenges. Every project I undertake aims not only to predict materials properties but to provide fundamental insights into the mechanisms governing materials behavior—insights that are essential for designing the next generation of energy materials.

Let's Connect on Research

I welcome discussions about potential research discussions, joint projects, academic opportunities, and knowledge exchange in computational materials science and sustainable energy applications.