Jan Kazil

Skills

Data Analysis - Data Science - Python - Computer Simulations - TensorFlow - Keras - NumPy - Pandas - Machine Learning - Convolutional Neural Networks (CNN) - Fortran - Climate Change - Grant Writing - Lead investigator - Neural Networks - Climate - Parallel Programming - Project Management - Applied Research - Weather - Forecasting - Atmospheric modeling - Climate modeling - Supervisory Skills - Computer Simulation - Numerical analysis - Numerical Modeling - Atmospheric Science - Climate Data Science - Atmospheric data analysis - Research Skills - Research and Development (R&D) - Global Warming - Operations Management - Team Management

About

I am an applied scientist with over 15 years of experience in high-resolution atmospheric modeling, numerical weather prediction models, and climate models. I am proficient in the workflow of atmospheric modeling starting from the design, implementation, and testing of model components, the design and operation of simulations on Linux HPC systems, to the analysis of very large and complex simulation datasets, including evaluation with observations. I have developed machine learning emulators of model components to accelerate the host model, implemented convolutional neural network solutions for satellite imagery instance segmentation, and a high-resolution climate model downscaling approach. I am proficient in Python and its various numerical, statistical, scientific, and ML libraries; in Fortran; and in parallel programming on HPC using MPI and OpenMP. I use Git as part of collaborative, version-controlled workflows.

I have honed my teamwork and communication skills in numerous interdisciplinary projects: e.g., in 2023 I led the weather forecast team during the NOAA/NASA AEROMMA aircraft field campaign, producing 24-hour forecasts from AWS-hosted HRRR and GOES satellite data, which facilitated planning and mission-critical decisions that contributed to mission success. My communication experience includes presenting complex scientific and technical concepts to technical and non-technical audiences, the general public, and stakeholders.