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NabKh/README.md

👋 Hi, I'm Nabil Khossossi (Nab)

Typing SVG

🔬 Postdoctoral Researcher | AI-Driven Materials Discovery | Computational Chemistry

Website Scholar LinkedIn ORCID

🔬 About Me

I am a theoretical chemist who is driven by curiosity in chemical complexity to develop novel methods and apply them to the understanding, design, and discovery of functional materials, molecules, and catalysts for energy-related applications. My computational arsenal includes quantum chemistry, statistical mechanics, parallelized and automated workflows, and data-driven approaches to investigate systems of different levels of complexity and spatial/temporal scales.

Current Research:

  • 🤖 AI4Mat Self-driving Laboratory for autonomous materials optimization
  • ⚡ Physics-informed ML for high-efficiency photovoltaic materials
  • 🧪 Multi-objective catalyst discovery using active learning

🤝 Let's Collaborate!

I'm actively seeking collaborations in:

  • 🔬 AI-driven materials discovery platforms
  • 🌱 Sustainable energy materials (solar cells, catalysts)
  • 🤖 Self-driving laboratories and autonomous experimentation
  • 📊 Large-scale materials databases and informatics

Looking for: Assistant Professor positions in computational materials science, ML for chemistry, and device acceleration platforms.

📧 Email: [n.khossossi@differ.nl & n.khossossi@hotmail.com]
🌐 Website: sustai-nabil.com
💼 Open to: Group leader/Senior Scientists | Faculty positions | Research collaborations | Consulting

"Bridging quantum mechanics, machine learning, and materials innovation"

⭐ Star my repositories if you find them useful!

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  1. OER-Free-Energy-GPAW OER-Free-Energy-GPAW Public

    This repository contains a Python script designed to perform Density Functional Theory (DFT) calculations to obtain the Oxygen Evolution Reaction (OER) free energy. The calculations are conducted u…

    Python 1

  2. SACs_HER_2024 SACs_HER_2024 Public template

    Python scripts for Few shot machine learning model to predict HER

    Python 2

  3. ML-for-Materials-Science ML-for-Materials-Science Public

    A comprehensive, interactive learning path for applying machine learning to materials discovery, property prediction, and atomistic simulations.

    Jupyter Notebook 2

  4. MXene-Structure-Generator MXene-Structure-Generator Public

    A Python framework for systematic generation and manipulation of MXene (M_{n+1}X_nT_z) crystal structures for computational materials science.

    Python 1

  5. Physics-Informed-ML-Solar-Cells Physics-Informed-ML-Solar-Cells Public

    A comprehensive tutorial and framework for applying physics-informed machine learning to photovoltaic materials discovery using Materials Project data.

    Jupyter Notebook