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Field
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, regardless of process parameters, it is essential to conduct a physical, chemical, and mineralogical analysis of the tailings to study the distribution of phosphates and their relationships with gangue
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the fate and distribution of contaminants in the environment. The researcher will be directly supervised by PI Cara Santelli, who has a diverse lab that is committed to inclusivity and creating a sense of
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Applicable Driver's License: A driver's license is not required for this position. More About This Job Required Qualifications: The applicant should have a PhD in biological/biomedical sciences, or an MD with
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a faculty member or researcher. External funding is currently available for one year. Typical hiring range for this soft-money funded position is $50,000 to $60,000 commensurate with qualifications
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, you supervise your students in courses about software architecture, software design, distributed systems engineering and software engineering. You are involved in organizing meetings, conferences and
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licence. Is Your profile described below? Are you our future colleague? Apply now! Education · You hold a PhD in Physics, Biology, Environmental Science, or a related discipline Experience and
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, software design, distributed systems engineering and software engineering. You are involved in organizing meetings, conferences and symposia. These are your qualifications: Must-haves: You have completed a
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distribution systems. The scholars will have a unique opportunity to work simultaneously on a real-world industry-grade microgrid and state-of-the-art Hardware-in-the-loop HIL testbeds. Essential functions
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postdoctoral researcher, you will use various techniques to investigate fiber-reinforced structures in nature (i.e., fungi), including additive manufacturing, computer simulations, materials testing, and
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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