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, including, but not limited to, quantum error correction, quantum optics, quantum algorithms, and atomic, molecular and optical physics. There are numerous research groups at Illinois Physics and across
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with disease and/or drug experts (clinicians, clinician scientists, data scientists, and laboratory investigators) to co-develop phenotyping algorithms but is expected to serve as the domain expert in
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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our group, you get the opportunity to use the latest algorithms in machine learning for improving
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academic academic achievements, especially first publications in the field of explainable AI with a focus on understanding algorithms by various stakeholders, especially at ACM FAccT, ACM AIES, International
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technology, big data analysis, and AI algorithm applications; show innovative thinking for solving complex system control challenges; be capable of interdisciplinary collaboration in microbiology and related
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of single-cell molecular data. Experience and expertise in ML/AI algorithms for analysis of single-cell genomic data Demonstrated capacity to work collaboratively with researchers across both dry and wet
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the development of fast and scalable algorithms for many-component systems, and of coarse-grained models that can be analyzed and simulated. Strong applicants with backgrounds in applied and computational
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of quantum field theory, mathematical aspects of string theory, general mathematical physics or quantum algorithms and quantum software development. We stress that candidates with an excellent research track
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sciences, who ad- dress key issues in AI such as reproducibility, safety, trustworthiness and robustness, and who engage with the theoretical and algorithmic foundations of AI. A strong commitment to
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-body positron emission tomography (PET) with magnetic resonance imaging (MRI). In conjunction with the development of algorithms, dedicated software and hardware-based simulations will be developed