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three courses per year, distributed according to the needs of the Department and upon mutual agreement. The appointee may be required to teach and develop courses on both undergraduate and taught
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research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential
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research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential
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publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential. Additionally, the candidate should possess an excellent
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background in AI—such as knowledge of machine learning or neural networks—will be an advantage. The appointee is expected to conduct focused research, publish scholarly outputs in reputable, peer-reviewed