Expertise in Machine Learning and Data Analysis. Modeling and simulation skills in Computational Material Science. Data-drive material discovery
Aktualisiert am 03.04.2024
Profil
Freiberufler / Selbstständiger
Remote-Arbeit
Verfügbar ab: 20.03.2024
Verfügbar zu: 100%
davon vor Ort: 100%
Big Data Analytics
Machine Learning
Deep Learning
Deep Neural Network
Analysefähigkeit
C++17
Python
MATLAB
Bourne-again-shell

Einsatzorte

Einsatzorte

Deutschland, Schweiz, Österreich
möglich

Projekte

Projekte

2 years 4 months
2021-09 - 2023-12

Study sequence-property relation using deep learning

Post Doctoral Researcher C++17 Python Bourne-again-shell
Post Doctoral Researcher
I investigated relationship between chemical sequence and material property using various neural network architecture.
Python PyTorch TensorFlow Keras SQL
C++17 Python Bourne-again-shell
Internal
Leibniz Institute for Polymer Research Dresden
3 years 1 month
2017-09 - 2020-09

Study mechanical properties of reversible cross-links

Doctoral student C++ Python
Doctoral student
Perform computational loading experiments to study the mechanical properties of reversible cross-link polymeric system.
Bourne-again-shell C++ Python
C++ Python
Wien Universität
1 year
2015-10 - 2016-09

Design, build, create in house application for computational experiments

Research Assistant C++ Python
Research Assistant
Wrote an in-house application in C++ from scratch. This application was employed to perform computational loading experiments in polymeric systems.
C++11 Python
C++ Python
Wien Universität

Aus- und Weiterbildung

Aus- und Weiterbildung

2 years 4 months
2021-09 - 2023-12

Material Informatics

Post Doctoral Researcher, Leibniz Institute for Polymer Research Dresden, Dresden, Germany
Post Doctoral Researcher
Leibniz Institute for Polymer Research Dresden, Dresden, Germany

Using Machine and deep learning, I study chemical sequence and material property relationships in various material. I employed various neural network (NN) architectures such as Feed Forward, GRU and Transformer NN to compare the performance of various networks. I study both forward and inverse problems through deep learning.

I used PyTorch, TensorFlow and Scikit-Learn machine learning libraries/frameworks for the deep learning.

4 years 11 months
2016-01 - 2020-11

Computational Material Science

Doctoral Degree, Wien Universität, Wien, Österreich
Doctoral Degree
Wien Universität, Wien, Österreich

Wrote an in house application in C++ that perform computational loading experiment to study deformation behavior and mechanical properties in polymeric systems. In the doctoral study, I used Python and bash extensively for data preprocessing, wrangling, numerical and statistical analysis, and visualization.

2 years 2 months
2013-09 - 2015-10

Computational Material Science

Master in Science (M.Sc), Ruhr Universität Bochum, Bochum, Germany
Master in Science (M.Sc)
Ruhr Universität Bochum, Bochum, Germany
In my master studies, I learned comprehensively about various computational methods used in the area of material science such as Finite Elements, Finite Difference, Phase Modelling, Monte Carlo, Molecular Dynamics, and Abintio calculations. I learned C++, Python, Bash and Matlab through different exercises.

Kompetenzen

Kompetenzen

Top-Skills

Big Data Analytics Machine Learning Deep Learning Deep Neural Network Analysefähigkeit C++17 Python MATLAB Bourne-again-shell

Programmiersprachen

C++
Experte
Python
Experte
Bash
Experte
MATLAB
Experte
PyTorch
Experte
TensorFlow
Experte
SQL
Experte

Einsatzorte

Einsatzorte

Deutschland, Schweiz, Österreich
möglich

Projekte

Projekte

2 years 4 months
2021-09 - 2023-12

Study sequence-property relation using deep learning

Post Doctoral Researcher C++17 Python Bourne-again-shell
Post Doctoral Researcher
I investigated relationship between chemical sequence and material property using various neural network architecture.
Python PyTorch TensorFlow Keras SQL
C++17 Python Bourne-again-shell
Internal
Leibniz Institute for Polymer Research Dresden
3 years 1 month
2017-09 - 2020-09

Study mechanical properties of reversible cross-links

Doctoral student C++ Python
Doctoral student
Perform computational loading experiments to study the mechanical properties of reversible cross-link polymeric system.
Bourne-again-shell C++ Python
C++ Python
Wien Universität
1 year
2015-10 - 2016-09

Design, build, create in house application for computational experiments

Research Assistant C++ Python
Research Assistant
Wrote an in-house application in C++ from scratch. This application was employed to perform computational loading experiments in polymeric systems.
C++11 Python
C++ Python
Wien Universität

Aus- und Weiterbildung

Aus- und Weiterbildung

2 years 4 months
2021-09 - 2023-12

Material Informatics

Post Doctoral Researcher, Leibniz Institute for Polymer Research Dresden, Dresden, Germany
Post Doctoral Researcher
Leibniz Institute for Polymer Research Dresden, Dresden, Germany

Using Machine and deep learning, I study chemical sequence and material property relationships in various material. I employed various neural network (NN) architectures such as Feed Forward, GRU and Transformer NN to compare the performance of various networks. I study both forward and inverse problems through deep learning.

I used PyTorch, TensorFlow and Scikit-Learn machine learning libraries/frameworks for the deep learning.

4 years 11 months
2016-01 - 2020-11

Computational Material Science

Doctoral Degree, Wien Universität, Wien, Österreich
Doctoral Degree
Wien Universität, Wien, Österreich

Wrote an in house application in C++ that perform computational loading experiment to study deformation behavior and mechanical properties in polymeric systems. In the doctoral study, I used Python and bash extensively for data preprocessing, wrangling, numerical and statistical analysis, and visualization.

2 years 2 months
2013-09 - 2015-10

Computational Material Science

Master in Science (M.Sc), Ruhr Universität Bochum, Bochum, Germany
Master in Science (M.Sc)
Ruhr Universität Bochum, Bochum, Germany
In my master studies, I learned comprehensively about various computational methods used in the area of material science such as Finite Elements, Finite Difference, Phase Modelling, Monte Carlo, Molecular Dynamics, and Abintio calculations. I learned C++, Python, Bash and Matlab through different exercises.

Kompetenzen

Kompetenzen

Top-Skills

Big Data Analytics Machine Learning Deep Learning Deep Neural Network Analysefähigkeit C++17 Python MATLAB Bourne-again-shell

Programmiersprachen

C++
Experte
Python
Experte
Bash
Experte
MATLAB
Experte
PyTorch
Experte
TensorFlow
Experte
SQL
Experte

Vertrauen Sie auf GULP

Im Bereich Freelancing
Im Bereich Arbeitnehmerüberlassung / Personalvermittlung

Fragen?

Rufen Sie uns an +49 89 500316-300 oder schreiben Sie uns:

Das GULP Freelancer-Portal

Direktester geht's nicht! Ganz einfach Freelancer finden und direkt Kontakt aufnehmen.