Evangelia Charvati-Postdoctoral Researcher & Data Steward
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Experience
Postdoctoral Researcher & Data Steward
Technical University Darmstadt (Müller-Plathe group)
- Developed and applied a symbolic regression scheme to explore and model complex relationships in liquid viscosities across their phase space, providing predictive insights into material properties.
- Contributed to the improvement of hybrid Particle-Field models through data-driven diagnostics and model enhancement strategies.
- Lead interdisciplinary collaboration with experimental physicists for the investigation of the molecular mechanisms behind water-based inks.
- Managed research data workflows to ensure public accessibility and institutional archiving of simulation data, code scripts, and inputs, directly supporting research transparency and reproducibility.
Teaching Assistant
Technical University Darmstadt & Zhiyuan Institute, Shanghai Jiao Tong University
- Cultivated a supportive and inclusive learning environment, receiving positive feedback for student engagement.
- Fostered a supportive and inclusive learning environment, developing curricula and assessment materials that maintained high academic standards and student engagement.
- Actively engaged in knowledge sharing and peer collaboration through teaching and direct mentorship on Bachelor thesis projects.
Ph.D. Researcher & CSC (Grade A) Scholar
Shanghai Jiao Tong University (Huai Sun group)
- Engineered a systematic, high-dimensional sampling framework for molecular configurations, generating robust datasets for predictive model training. Integrated machine learning to optimize parameter fitting, significantly enhancing model generalization and predictive power for complex structures.
- Tailored and optimized force field parameters for the complex biomaterial cellulose-Iβ, achieving unprecedented accuracy in crystal lattice and thermodynamic property predictions, surpassing existing models.
- Successfully engineered, benchmarked, and validated simulation-ready, physics-informed models that accurately predict system behavior across diverse thermodynamic regimes.
- Automated molecular structure transformation from fine-grained to coarse representations using a novel graph-theoretical algorithm, improving efficiency in multi-scale simulations.
Industry experience
See where this freelancer has spent most of their professional time.
Experienced in Education and Chemical.
Business area experience
See which departments and functions this freelancer has contributed to most.
Experienced in Research and Development.
Summary
Data-driven Computational Chemist with a Ph.D. in Physical Chemistry and expertise in machine learning, statistical modeling, molecular dynamics simulations, and high-performance computing.
Skilled in transforming complex datasets into actionable insights and scalable solutions. My interests include photography and hiking.
Skills
- Programming: Python (Numpy, Pandas, Scikit-Learn, Tensorflow, Seaborn, Matplotlib, Rdkit, Networkx), Bash Scripting, Scientific Computing, Data Pipelines, Workflow Automation, Version Control (Git), Code Modularization.
- Data Science & Engineering: Machine Learning, Regression, Statistics, Pandas, Symbolic Regression (Gplearn), Convolutional Neural Networks, Preprocessing, High-Throughput Data Generation, Sql Database, Nosql, Statistical Modeling, Dimensionality Reduction, Model Validation, Visualization, Graph Theory.
- Data Management: Data Curation, Version Control, Code Management, Metadata, Reproducibility, Data Accessibility, Fair Principles.
- High Perfromance Computing: Hpc Job Schedulers (Slurm, Pbs).
- Atomistic Force Field Development: Force Field Development And Validation, Interatomic Potentials, Energy Function Optimization, Ab-Initio Calulculations, Thermodynamic Properties Prediction.
- Molecular Simulation Software: Gaussian, Gromacs, Lammps, Galamost, Chemdraw.
- Software: Git, Slurm, Linux, Latex, Microsoft Office.
- Communication: Academic Writing, Public Speaking, Scientific Storytelling, Knowledge Sharing.
- Soft Skills: Mentorship, Peer Collaboration, Cross-Cultural Communication.
Languages
Education
Shanghai Jiao Tong University
Ph.D. · Physical Chemistry · Shanghai, China
University of Bordeaux
Master of Science · Bordeaux, France
University of Bordeaux
Bachelor's Degree · Chemistry · Bordeaux, France
Statistics
Experience
Expertise
Qualifications
Profile
Frequently asked questions
Have questions? Find more information here.
Evangelia is based in Darmstadt, Germany.
Evangelia speaks the following languages: Greek (Advanced), English (Advanced), French (Advanced), German (Elementary), Chinese (Elementary).
Evangelia has at least 8 years of experience. During this time, Evangelia has worked in at least 3 different roles and for 3 different companies. The average length of individual experience is 3 years and 8 months. Note that Evangelia may not have shared all experience and actually has more experience.
Based on recent experience, Evangelia would be well-suited for roles such as: Postdoctoral Researcher & Data Steward, Teaching Assistant, Ph.D. Researcher & CSC (Grade A) Scholar.
Evangelia's most recent position is Postdoctoral Researcher & Data Steward at Technical University Darmstadt (Müller-Plathe group).
In recent years, Evangelia has worked for Technical University Darmstadt (Müller-Plathe group), Technical University Darmstadt & Zhiyuan Institute, Shanghai Jiao Tong University, and Shanghai Jiao Tong University (Huai Sun group).
Evangelia is most experienced in industries like Education and Chemical.
Evangelia is most experienced in business areas like Research and Development.
Evangelia has recently worked in industries like Education and Chemical.
Evangelia has recently worked in business areas like Research and Development.
Evangelia holds a Doctorate in Physical Chemistry from Shanghai Jiao Tong University, a Master from University of Bordeaux and a Bachelor in Chemistry from University of Bordeaux.
The availability of Evangelia needs to be confirmed.
Daily rate distribution
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Average rates for similar positions
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The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 7 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
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