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) for science with Dr. Aleksandra Ciprijanovic (alexciprijanovic.com) and her research group! The successful candidate will join a multidisciplinary team working at the intersection of deep learning, cosmology
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students. The rest of your time (40%) is devoted to teaching. The department has developed several courses within data science, e.g., Bayesian methods, Advanced Machine Learning, Deep Learning and AI methods
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of Students & Learning Innovation to attract and enroll diverse candidates across the school’s educational programs. Support efforts to build a pipeline of diverse students from community organizations, other
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deep experience with PyTorch, JAX, or TensorFlow. Broad knowledge of modern ML and optimization (gradient‑based, evolutionary, Bayesian, reinforcement learning). Hands‑on experience with generative
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in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will be contributing to the BESSER
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, applications, tools, and services for the broader research community to use data at scale to pursue scientific inquiry and accelerate discovery. Learn more at https://gdc.cancer.gov/ , https://gen3.org/ , https
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program , and an institutional membership to the Center for the Integration of Research, Teaching and Learning . To learn more visit: https://engineering.osu.edu/faculty-development . Learn more about
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development, in particular with courses on condensed matter physics, quantum materials and muon science, and supervising PhD students as well as Bachelor and Master theses. The successful candidate will head
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located in the heart of Detroit, Michigan where students from all backgrounds are offered a rich, high-quality education. Our deep-rooted commitment to excellence, collaboration, integrity, creates
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arrays) from experimental data, leveraging training on simulated datasets. Interpretable neural networks for physics: Development of interpretable deep learning models for identification of matter phases