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Position Description Flatiron Research Fellow, Biophysical Modeling, Center for Computational Biology Flatiron Institute - Simons Foundation Location 162 5th Avenue, NY, NY 10010 Open Date Sep 16
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Engineering, Computer Science, or a related field. Proven experience working with wireless sensors, point cloud data processing, and sensor integration. Strong background in signal processing, computer vision
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The VCC center at KAUST is looking for postdoctoral researchers and research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer graphics, and deep
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-based applications (e.g., AWS, Google Cloud, Microsoft Azure), including containerization (Docker), orchestration (Kubernetes), serverless computing, and REST API development. Proficient in Python, with
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AI models to automate QA/QC processes, enabling real-time verification, anomaly detection and consistency checks across records. Develop a cloud-based verification platform for digital data collection
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The Japan Society for the Promotion of Science (JSPS) has established the JSPS Postdoctoral Fellowships for Research in Japan – Standard program. A limited number of promising early career
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of Computing and Data Science (CCDS) at NTU. Technical skills, natural curiosity, versatility, and enthusiasm are highly desired traits that will enable success in this fast-paced environment. Key
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role in advancing the research agenda. Your responsibilities will include: · Perform research on computational modeling of EF-hand proteins · Perform method development for relevant systems of EF-hand
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 12 hours ago
structured learning opportunities in regulatory science and computational modeling applications in drug development and use of artificial intelligence for data mining. You will gain experience in regulatory
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, and AI-driven computational biology. The successful candidate will develop and apply innovative computational methods to analyse large-scale multi-omic datasets, identify mutational patterns across