Curriculum Vitate
A comprehensive overview of my academic journey, professional experience, and key achievements
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🎓 Education
Doctoral Researcher in Computational Physics
University of Freiburg, Freiburg, Germany
2020-2025
Graduated with Magna Cum Laude
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Master in Physics (Material Science Focus)
Indian Institute of Technology (IIT) Gandhinagar, India
2018-2020
GPA 8.53/10.0
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Bachelor in Physics
Thakurpukur Vivekananda College, University of Calcutta, India
2018-2020
Graduated with First Class Honours
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📈 Experience
Doctoral Researcher in Computational Physics
University of Freiburg, Freiburg, Germany
2020-2025
Research projects using molecular dynamics and first-principles calculations to elucidate structure–property relationships in complex molecular materials.
Developed and deployed multi scale DFT–MD workflows for modelling polymeric and electrochemical interfaces, linking atomistic structure to macroscopic properties.
Parameterised and validated custom force fields capturing complex non-covalent interactions (e.g. cation-π and solvation effects) for interfacial polymer systems.
Performed large-scale molecular dynamics simulations (LAMMPS) and electronic structure calculations (FHI-aims, VASP) on HPC clusters to study electrode–electrolyte interactions.
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Teaching Assistant
University of Freiburg, Freiburg, Germany
2021-2023
Classical Electrodynamics -- (Skills: Electrostatics and electrodynamics, supporting student learning, assessments of weekly assignments)
Computational Physics: Material Science -- (Skills: Statistical mechanics, Molecular Dynamics, Code development, Debug supporting)
Classical Complex Systems -- (Skills: Statistical mechanics, Monte Carlo Simulation, Molecular Dynamics, Code development)
Theoretical Condensed Matter Physics -- (Skills: Structure of solids and liquids, classical density functional theory, soft and charged condensed matter)
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Master Thesis Research
Institute of Technology Gandhinagar, India
2019-2020
Performed density functional theory calculations to evaluate structural stability, electronic properties, and ion-interaction energetics of novel two-dimensional anode materials for energy storage.
Gained proficiency in first-principles modelling (Quantum ESPRESSO) and solid-state physics analyses, laying the groundwork for subsequent multi scale simulation work.
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Reseach Internship
Japan Advanced Institute of Science & Technology
May-July, 2019
Conducted DFT simulations on 2D materials and metal interfaces to investigate adsorption geometries and electronic interaction effects.
Strengthened skills in computational toolchains (VASP, Python) and cross-cultural research collaboration within an international lab environment.
🎯 Core Expertises
Physics-Based modelling
LAMMPS MDAnalysis Ovito VASP GAMESS-US FHI-aims Quantum Espresso Polymers Electrolytes Soft-materials
Multiscale Simulation
DFT-to-MD coupling Ab initio MD
Force Fields & Potentials
Interatomic potential - Charge, Dihedral, Cation-π interaction
Machine learning force field - MACE , DEEPMD
Data-Driven Modeling
Graph neural networks
PyTorch Tensor flow Scikit-learn
High-performace computing
HPC environments Large datasets
Programming
Python (Numpy, Pandas, ASE, MDAnalysis, PyTorch), Bash Scripting, Git version
Communication
Scientific writing Scientific presentations
Languges
English: Fluent
German: Intermediate
Bengali: Native
⭐ Certifications & Training
Structuring Machine Learning Projects
Skills learned -
Diagnose errors in a machine learning system
Understand complex ML settings
Apply end-to-end learning
Transfer learning
Certificate link - Coming soon
Github link - Coming soon
Convolution Neural Networks
Skills learned -
Build convolutional neural network (CNN)
Apply CNN to visual detection and recognition tasks
Use neural style transfer to generate art
Residual networks
Certificate link - Coming soon
Github link - Coming soon
PyTorch for Deep Learning Bootcamp
Skills learned -
PyTorch Fundamentals
PyTorch Workflow
PyTorch Neural Network Classification
PyTorch Computer Vision
Certificate link -
Github link - Link
Introduction to AI and ML on Google Cloud
Skills learned -
Data-to-ai Technologies
Build ML models end-to-end by using Vertex AI
Use Generative AI capabilities.
Certificate link - Link
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