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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Genomics, Transcriptomics, and Bioinformatics Department Bashashati Laboratory | School
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We are seeking creative and energetic candidates with strong experience in multimodal machine learning and human behavior analysis and modeling for a one-year Postdoctoral position. Using recent
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at the John Curtin School of Medical Research (JCSMR), within the ANU College of Science and Medicine. This role will lead the development of advanced deep learning frameworks—including graph neural networks
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a Research Infrastructure? No Offer Description The Department of Ecology, Environment and Plant Sciences (DEEP) is located in the Arrhenius Laboratories, situated at the University Campus at Frescati
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of genome organisation and metabolic control - with the bold vision of building synthetic life. In this role, you will develop and apply deep learning methods to analyse single-cell modalities, focusing
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of building synthetic life. In this role, you will develop and apply deep learning methods to analyse single-cell modalities, focusing on gene regulation and the engineering of microbial and human cells. You
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Learning, or a related field. For Postdoctoral Fellows: A completed PhD in one of the fields mentioned above and a strong publication record. Strong programming skills in Python and practical experience with
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About the Opportunity About the Opportunity Northeastern University Pharmaceutical Industry Fellowships Program is a two-year experiential program designed to advance lifelong learning and the
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Internal Number: 6563165 Vertex Pharmaceuticals-US Market Access Postdoctoral Research Fellow About the Opportunity About the Opportunity Northeastern University Pharmaceutical Industry Fellowships Program
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Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique, | Palaiseau, le de France | France | 13 days ago
(denoising, Mueller matrix calculation/decomposition) and AI-based diagnostic algorithms using machine/deep learning. The primary challenge will be to deliver practitioner-relevant cervical images in under 0.5