64 algorithm-development-"Multiple" "NTNU Norwegian University of Science and Technology" Postdoctoral positions at Stony Brook University
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intelligence or machine learning from other fields. Candidates seeking to bridge multiple disciplines or bring AI into new scientific/applied domains are particularly encouraged to apply. We will process
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equipment. This position involves both technical and research support responsibilities. The successful candidate will contribute to method development, target and non-target analysis of environmental
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equipment. This position involves both technical and research support responsibilities. The successful candidate will contribute to method development, target and non-target analysis of environmental
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Postdoctoral Scholar, named in honor of Dr. Meave Leakey’s extraordinary contributions to the understanding of human and primate evolution in the Turkana Basin, will join the SHaPE (Studies in Human and Primate
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applicants may select from multiple projects and should have experience in most of the following areas: ● Background in cell/molecular biology. ● Experience with mouse models. ● Experience with
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Postdoctoral Scholar, named in honor of Dr. Meave Leakey’s extraordinary contributions to the understanding of human and primate evolution in the Turkana Basin, will join the SHaPE (Studies in Human and Primate
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intelligence, AI-based data analysis, transcriptomics, proteomics, genomics or spatial omics. Interdisciplinary background or interest. A focus on Wet Lab research development. Candidates with experience
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intelligence, AI-based data analysis, transcriptomics, proteomics, genomics or spatial omics. Interdisciplinary background or interest. A focus on Wet Lab research development. Candidates with experience
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neurological conditions. The Postdoctoral Associates primarily will be responsible for developing human clinical research protocols and preparing applications for IRB, RDRC, or IND, collecting PET and/or MRI
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models, with a focus on their applications to next-generation MR image reconstruction. Train deep neural networks; perform quantitative data analysis, collect and analyze data, including periodic