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techniques to challenging biological systems. Requirements: Ideal candidates should hold an excellent PhD in structural biology, biochemistry, biophysics or in an equivalent area. Experience in membrane
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
holder will also co-supervise a PhD student who will be involved in the same project. This is a highly interdisciplinary project combining forest ecology, remote sensing, machine learning, epidemiology
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on applying, developing and implementing novel statistical and computational methods for integrative data analysis, causal inference, and machine/deep learning with GWAS/sequencing data and other types of omic
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analysis Close collaboration with an interdisciplinary team. Research and teaching efforts at a section and departmental level as appropriate and relevant (e.g., teach and supervise MSc and PhD student
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high intellectual merit and the willingness to use machine learning and/or AI techniques. Essential Duties and Responsibilities: Successful candidates are expected to develop an impactful research
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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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project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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students and technicians Maintain accurate documentation of protocols and instrument logs; liaise with service and facility management Your profile: PhD (or equivalent) in analytical/biological chemistry
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on reliability, security, and resilience of electric power systems and microgrids and stability analysis and Scientific Machine Learning (SciML) for microgrid applications. The successful candidate will be