Data Scientist (Deep Learning and Computer Vision)
Aktualisiert am 03.11.2023
Profil
Freiberufler / Selbstständiger
Remote-Arbeit
Verfügbar ab: 01.11.2023
Verfügbar zu: 100%
davon vor Ort: 0%
Python
PyTorch
OpenCV
Computer Vision
Deep Learning
Generative AI
Data Analysis
Data Visualization
C++
scikit-learn
Diffusers
Transformers
NLTK
Git
NumPy
SciPy
Matplotlib
German
Muttersprache
English
Verhandlungssicher

Einsatzorte

Cologne (+50km)
Deutschland, Schweiz, Österreich
möglich

Projekte

2 Jahre 8 Monate
2020-02 - 2022-09

Research in Theoretical Nuclear Physics

Research Assistant Python Deep Learning
Research Assistant
  • Investigation of quantum mechanical few-body systems using machine learning techniques.
  • Simulation of scattering events, preparation of training and test data sets, and statistical evaluation of trained neural networks.
  • Dimensionality reduction of high-dimensional data sets via self-supervised learning and subsequent optimization in low-dimensional latent spaces.
  • Publication of peer-reviewed articles in and correspondence with scientific
    journals.


Publications:

  • Apr. 20, 2022: Bastian Kaspschak and Ulf-G. Meißner, Three-body renormalization group limit cycles based on unsupervised feature learning, Machine Learning: Science and Technology 3, 025003.
  • Jun. 21, 2021: Bastian Kaspschak and Ulf-G. Meißner, Neural network perturbation theory and its application to the Born series, Physical Review Research 3, 023223.
  • Feb. 04, 2021: Bastian Kaspschak and Ulf-G. Meißner, How machine learning conquers the unitary limit, Communications in Theoretical Physics 73.3, 035101.


Workshops:

  • Jun. 9 ? 10, 2022: Advanced Deep Learning Train-the-Trainer Workshop at the University of Wuppertal, organized by DIG-UM and the ErUM-Data-Hub.
  • Mar. 30 ? 31, 2022: Deep Learning Train-the-Trainer Workshop at the RWTH Aachen, organized by DIG-UM and the ErUM-Data-Hub.
  • May 25 ? 28, 2021: Lecture Series on Machine Learning in High Energy Physics, organized by the Bethe Center for Theoretical Physics, Bonn.
PyTorch
Python Deep Learning
University of Bonn
Bonn
7 Jahre
2015-10 - 2022-09

BSc. Physics Tutoring

Tutor
Tutor
Various tutoring activities in theoretical electrodynamics, theoretical quantum mechanics
and complex analysis.
University of Bonn
Bonn

Aus- und Weiterbildung

1 Jahr 3 Monate
2018-10 - 2019-12

Master of Science in Physics

MSc. (1.8), University of Bonn
MSc. (1.8)
University of Bonn
Master thesis: How machine learning conquers the unitary limit (1.0)
4 Jahre
2014-10 - 2018-09

Bachelor of Science in Physics

BSc. (2.2), University of Bonn
BSc. (2.2)
University of Bonn
Bachelor thesis: Representations of the cubic group in lattice gauge theories (1.0)
2 Jahre
2012-10 - 2014-09

Early Study Program

University of Bonn
University of Bonn
Participated in an Early Study Program program, financed by the Deutsche Telekom Foundation, during my final two years of high school, attending physics lectures, and successfully earning credits that were later transferred upon my official enrollment.

Position


Kompetenzen

Top-Skills

Python PyTorch OpenCV Computer Vision Deep Learning Generative AI Data Analysis Data Visualization C++ scikit-learn Diffusers Transformers NLTK Git NumPy SciPy Matplotlib

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