Pablo Grobas Illobre
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Pablo Grobas Illobre, PhD

Experienced researcher with 6+ years of expertise in computational quantum chemistry, specialized in the development and application of QM/MM methodologies in the context of biosensor design. Skilled in Python, C++, and Fortran, with a strong track record in scientific software development, data analysis, manipulation, and visualization. Now seeking to apply this expertise in drug discovery, with a growing interest in applying machine learning and data science to molecular modeling and cheminformatics.

Technical Skills

  • Languages: Python, C++, Fortran, Matlab
  • Libraries: NumPy, SciPy, TensorFlow, PyTorch
  • Tools: Git, Vim, VS Code
  • Scripting: Bash, Linux
  • Scientific SW: AMS, Gaussian
  • HPC: Cluster environments

Experience & Training

Postdoctoral Researcher,

Scuola Normale Superiore (Pisa, Italy)

02/2025 – Present

Currently developing QM/MM quantum chemistry software in C++ and Fortran in collaboration with the Software for Chemistry & Materials company. This work is complemented by Python programming for machine learning, data analysis, statistics, and visualization.

My research integrates intensive software development to investigate:

  • QM/MM Surface-Enhanced Spectroscopies: fluorescence, Raman scattering, Raman optical activity.
  • Plasmonic Materials: graphene & metal nanoparticles.
  • Plasmon-Mediated Electronic Energy Transfer.
Working languages English · Italian

Research Projects

SCM (Software for Chemistry & Materials) logo

Development of Quantum Chemistry Software for SCM (Software for Chemistry & Materials)

Industry collaboration associated with Scuola Normale Superiore | Nov 2020 – Present
  • Algorithms for Surface-Enhanced Raman Scattering (SERS).
  • Methods for Surface-Enhanced Fluorescence (SEF).
  • Tools for plasmon-mediated resonance energy transfer.
  • Implementation of Surface-Enhanced Raman Optical Activity (SEROA) calculations.
FARE logo

FARE — “Framework per l’attrazione e il rafforzamento delle eccellenze per la ricerca in Italia”

Scuola Normale Superiore | 2020 – 2025 | PI: Chiara Cappelli

  • Python programming (in-house codes) for data analysis, manipulation, and visualization (e.g., Python-driven figures in P. Grobas Illobre et al., Nanoscale Adv., 2024, 6, 3410 ).
  • Quantum chemistry QM/MM software development in C++ and Fortran (AMS + in-house) for surface-enhanced fluorescence and plasmon-mediated electronic energy transfer.
  • Intensive use of HPC infrastructures to automate and streamline data production workflows.
GEMS logo

GEMS — General Embedding Models for Spectroscopy ,

ERC Consolidator Grant

Scuola Normale Superiore | 2020 – 2025 | PI: Chiara Cappelli

  • Python programming (in-house codes) for data analysis, manipulation, and visualization (e.g., Python-driven figures in T. Giovannini et al., ACS Photonics, 2022, 9, 3025 ).
  • Currently developing a machine learning pipeline in Python to study and simulate graphene samples.
  • Quantum chemistry software development in Fortran (Amsterdam Modeling Suite + in-house) for plasmonic materials, QM/MM SERS, and Raman optical activity.
  • Intensive use of HPC infrastructures to streamline large-scale data production workflows.
See related softwares →

Selected Publications

  • Nanoscale Advances (2024)

    P. Grobas Illobre , P. Lafiosca , T. Guidone , F. Mazza , T. Giovannini , C. Cappelli

    We present the first fully atomistic multiscale method (QM/uFQFμ) to model surface-enhanced fluorescence (SEF) of molecules near plasmonic nanostructures. By coupling quantum mechanics with an atomistic electrodynamical model, the approach captures how nanoparticle morphology, defects, and atomistic features control fluorescence quenching and enhancement.

    QM/MM · Fortran · Python · AMS · SEF · HPC · PlasmonX
    Read the article →

  • The Journal of Chemical Physics (2025)

    P. Grobas Illobre , P. Lafiosca , L. Bonatti , T. Giovannini , C. Cappelli

    We introduce a hybrid multiscale method (ωFQFμ-BEM) that models metal nanoparticles with an implicit continuum core and atomistic surface. Coupled with quantum mechanics, this framework reproduces optical properties and Surface-Enhanced Raman Scattering (SERS) with high accuracy at a fraction of the computational cost of fully atomistic approaches

    QM/MM · Fortran · Python · AMS · SERS · HPC · PlasmonX
    Read the article →
See all publications →

Awards

  • PhD awarded with honors (cum laude).
  • Scuola Normale Superiore PhD Scholarship (2020–2025).
  • Two NanoX Research Scholarships (2019 & 2020).
  • Erasmus Internship Fellowship (2019–2020).
  • Consejo Superior de Investigaciones Científicas (CSIC) – Jae Intro Fellowship (2019).
  • Extraordinary Prize for achieving the best academic record in the Bachelor of Chemistry (2018).
  • Erasmus+ scholarship (2016).