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‘best-practices’ in semiconductor processing. Qualifications A successful candidate should have: M.S. or PhD in Physics, Electrical Engineering, Materials Science, or related Engineering discipline
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in computational biology, biomedical engineering, bioinformatics, computer science, statistics, or a related field. Strong background in machine learning, data integration, and high-dimensional data
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Qualifications: We seek exceptionally strong candidates with a PhD in statistics, biostatistics, computer science or a related field. Candidates with demonstrated accomplishment in academic research, as can be
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, engineering, or chemistry prior to the start date. Please email Prof. Lee R. Liu at leeliu@purdue.edu with your CV, contact information for 2-3 references, and a brief research statement outlining your
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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Sequencing (GBS), Whole Genome Sequencing (WGS) and targeted genotyping chips (e.g. MassArray) and analyze them together with environmental data using population genetics and machine learning tools
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, Physics , Quantum Computation , Quantum Computing , Quantum Condensed Matter Theory , Quantum error correction , Quantum Field Theory , Quantum Information , Quantum Information Processing and Communication
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Purdue’s strategic focus on health equity and population health. Program Goals and Learning Objectives The fellow will gain experience in: Designing and conducting pharmacoepidemiologic studies in cancer and
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the culture of the College of Liberal Arts (#ThinkBroadlyLeadBoldly). Pay band: In addition to annual salary of up to $75,000, this position provides office space, computer equipment, and $2500 in yearly
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addition to annual salary of up to $75,000, this position provides office space, computer equipment, and $2500 in yearly support for scientific conferences or professional development. A sign-on bonus will also be