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Field
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critical role in advancing computational materials science by developing and applying first-principles and machine learning methods, with a focus on interatomic potential development and large-scale
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magic, quantum circuits, quantum algorithms (3) Quantum many body computations, including sign problem theory, Quantum Monte Carlo method, DMRG, and machine learning Appointments of postdoctoral
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to junior researchers, graduate students, and lab technicians, fostering an environment of learning and collaboration. Statement In this position, the Postdoctoral Fellow will frequently encounter complex
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identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision
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to mentor students, teach/train other researchers in LCA tools, and develop independent research projects as desired. The successful applicant will possess a PhD in chemical engineering, chemistry
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. The appointee will primarily conduct research applying advanced machine learning/AI (including techniques like deep learning) to analyze complex biological and clinical data (e.g., single-cell multi-omics
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experiments in the field of neuroscience, computational neuroscience and biologically plausible machine learning tools. Duties: Analyze data and developing biologically plausible machine learning frameworks
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will be determined based on factors including (but not limited to) the qualifications of the selected candidate, budget availability, and internal equity. Pay Range: $86,100 Aligning Machine Learning
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. · Experience in collaborations with experimental organic and biocatalysis research groups. · Experience in using machine learning tools in chemical research. · Expertise in using a variety of
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The Institute for Complex Social Dynamics (ICSD) and the Machine Learning Department at Carnegie Mellon University are seeking a talented and motivated postdoctoral researcher for a joint position