Qualifications
- Currently enrolled in a Masters or a PhD program in STEM subjects (e.g. materials science, chemistry, chemical engineering, mechanical engineering, computer science, systems engineering, public policy, energy economics, or a related discipline with an emphasis on computational research)
- Experience with ML: supervised learning: neural networks (e.g. classification, LSTM), Unsupervised: Clustering (e.g. k-means, hierarchical), and/or reinforcement (e.g. Markov decision process, discrete choice model)
- Experience with platforms like SciPy, PyTorch, Tensorflow; GIS is a bonus
- Demonstrated interest in decarbonization, technoeconomics, and policy
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