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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 1 day ago
College of Business and Economics. The successful candidate will undertake a collaboratively designed research program in statistical design and modelling, while also providing analytical support to
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Program and will work closely with the staff of the Image Collection and Fieldwork Archives (ICFA) to process the Justin Kerr Collection, which consists of photographs of approximately 6,000 unique
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underlying the processing of natural visual stimuli, using in vivo large-scale two-photon calcium imaging and virtual reality in awake behaving mice. Analyse in vivo large-scale two-photon calcium imaging data
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Details Title Postdoctoral Fellow in Pre-Columbian Art/Archaeology at Dumbarton Oaks/Harvard University School Faculty of Arts and Sciences Department/Area Dumbarton Oaks Position Description
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quantitative image analysis approaches. Excellent molecular biology skills. Strong interest and experience in using interdisciplinary approaches in their research program. Excellent written and oral
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process can be directed to Prof. Chen-Ting Liao (Liao3[at]IU.edu) Basic Qualifications: • Ph.D. in Physics, Chemistry, Quantum Information Science, Optics, Electrical Engineering, or a related field at the
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well as experimental and computational approaches. The ideal candidate will have a strong interest in gene regulatory mechanisms, with a track record of creative research in molecular biology, cell biology, genomics
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learning, as well as in digital signal processing and acoustic imaging. The group includes around 20 postdoctoral researchers and PhD research fellows funded by a range of national and international agencies
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topic, that includes geophysics, mathematics, physics, computer science or any related topics with a track record in relevant applications (processing, imaging and inversion). In addition to initiating
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: PhD degree in Computer Science, Electrical Engineering, or a closely related field Strong research background in computer vision and deep learning Solid experience with multimodal learning, segmentation