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existing experimental results and guide the design of future carbon-based electronic and optoelectronic devices. Requirements: Education: Master in materials science or engineering, PhD in materials science
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subject. Proven experience with X-ray imaging/diffraction techniques, e.g. XRD-CT, 3D-XRD, µ/nanoCT, STXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability
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will not be pre-assessed or pre-evaluated via email or phone; Only applicants with research experience (during or after their PhD) related to nature-based solutions, social innovation, or community
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all requirements for the PhD degree or a letter signed by your dissertation advisor indicating that you will complete the PhD by the start date of the fellowship. *The names and email addresses of three
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contributing to academic publications and wider dissemination. The successful candidate will have a PhD, or be near completion of a PhD in a discipline relevant to high-stakes regulated domains, such as
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on-site, along with their associated supportive technologies (such as solar photovoltaics, solar thermal systems, wind power, renewable fuels, geothermal solutions, battery storage, thermal storage, and
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. Demonstrated interest in, and ability to engage with, social science and humanities literature relevant to AI system design (e.g., ethics of AI, human-computer interaction, deliberative quality) 6. A clear
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area: Development of bioinspired antioxidants based on betalain molecular scaffolds; reactivity toward reactive oxygen/nitrogen species and electronically excited (triplet) states; photobiological
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guidance to PhD students and junior researchers. Candidate profile: The ideal candidate enjoys tackling challenging biological questions, thinks creatively about experimental design, and is eager to develop
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commitment to integrating AI in their scholarship and instruction and may come from any discipline. A PhD is expected prior to the start date. The Postdoctoral Scholar will serve as one of the Initiative’s AI