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studying deformation mechanisms in refractory alloys as via atomic-scale calculations as well as application of machine learning to materials discovery The ideal candidate will have the following
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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’ achievement of the learning objectives. Education and Experience Requirements Required : Advanced Degree (MFA, MA, PhD) in Theatre, Stage Management, or comparable field/graduate degree. Desired: Teaching
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tenure-track faculty hire in theoretical/computational biological physics. Candidates who incorporate machine learning approaches into their research program are especially encouraged to apply
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advanced machine learning and deep learning tools to decode the complexity of immune–tumor interactions, integrate multi-omics data at scale, and predict patient responses to therapy. The center works at
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. Demonstrated expertise in interdisciplinary research with technical and clinical teams and patients desired. Experience leveraging machine learning for human musculoskeletal biomechanics applications desired
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Molecular Pathology at the Full Professor rank. Expertise in molecular pathology, clinical bioinformatics/informatics, and genomics is essential. Research interests in machine learning, artificial
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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data Experience with GIS/RS and database environments (e.g., ArcGIS and Quantum GIS) Experience with machine learning and statistical learning Experience working with large, diverse datasets Familiarity