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  • ETH Zürich
  • Zürich
  • 02:26 (UTC +02:00)

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nviebig/README.md

Hey there :)

Im Niklas, a Physics MSc student at ETH Zurich interested in numerical simulation, differentiable models, and scientific machine learning.

My focus is on making high-performance atmospheric models differentiable, enabling gradient-based inference, calibration, and sensitivity analysis in climate and planetary systems.

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💻 Tech Stack

Languages & Tools
Julia Python C++ LaTeX

Scientific & ML
PyTorch TensorFlow Keras NumPy SciPy scikit-learn Pandas Matplotlib Plotly mlflow

Dev & Version Control
Git GitHub GitLab

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  1. SpeedyWeather/SpeedyWeather.jl SpeedyWeather/SpeedyWeather.jl Public

    Play atmospheric modelling like it's LEGO.

    Julia 550 61

  2. Bayesian-SpatioTemporal-Modeling Bayesian-SpatioTemporal-Modeling Public

    This project models Brazilian wildfires using Bayesian methods, analyzing meteorological and land-use data over a decade. Conducted for ETH Zurich’s Bayesian Statistical Methods and Data Analysis H…

    Jupyter Notebook 1

  3. LorenzParameterEstimation LorenzParameterEstimation Public

    Julia package for parameter estimation in the Lorenz-63 chaotic system using automatic differentiation with Enzyme.jl. Includes RK4 integration, windowed training with teacher forcing, gradient cli…

    Jupyter Notebook