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The detection of chemical cues from the outside world is fundamental to animal survival. In mammals, sensing of the external chemical environment governs diverse behaviours including selection of food, social
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develop innovative solutions based on the analysis of urban data (big data, IoT, GIS) to monitor and improve public health. You will contribute to modeling smart cities with a focus on health and designing
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The detection of chemical cues from the outside world is fundamental to animal survival. In mammals, sensing of the external chemical environment governs diverse behaviours including selection of food, social
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the workpackage team and collaborating with partners across Europe: data sharing, code exchange, joint publications. Your qualities You hold a PhD (or near completion) in statistics, applied mathematics, data
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qualifications as specified by the Principal Investigator. PREFERRED QUALIFICATION: PhD. NOTE: Position tasks are generally required to be performed in-person at an Emory University location. Remote work from
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Metropolitan University welcomes those who have demonstrated a commitment to upholding the values of equity, diversity, and inclusion and will assist us to expand our capacity for diversity in the broadest sense
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) Participation in international conferences (including presenting your research results) Preparation of scientific publications and project reports Supervision of PhD students and other students Support in
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in sustainability, photonic and quantum technologies, new nanostructured materials, sensing, imaging and clean energy. The group adopts an interdisciplinary approach to provide leading-edge research in
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criteria PhD in Neuroscience or near to completion* At least one first-author publication in a scientific journal Extensive experience working with mice Extensive experience analysing single-cell RNA
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. Contribute to the supervision of master and PhD students. Qualifications: Ph.D. in Earth Sciences, Remote Sensing, Physics, Applied mathematics, or related field. Strong background in land surface modeling