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, beginning with Parkinson’s disease. The successful candidate will serve as a data manager to liaise between the project’s different data generating and database development teams and facilitate
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to develop deep learning models for analyzing whole-slide histopathology images, as well as natural language processing (NLP) methods for clinical records such as pathology reports and electronic health data
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. Perform data management, large-scale statistical analyses, and ensure high standards of documentation and reproducibility. Work effectively with colleagues across the CTP and with local and international
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spearhead data integration and analysis of a growing multi-‘omic dataset designed to study healthy aging, Parkinson’s Disease, and other age-related conditions. ORGANIZATIONAL STATUS The CMMI is a large
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part of the core PLI team, which includes top-tier faculty, research fellows, scientists, software engineers, postdocs, and graduate students. Fellows will have access to the AI Lab GPU cluster (300
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implement analytical pipelines for data preprocessing, quality control, normalisation, clustering, differential expression, trajectory inference, and pathway enrichment analyses. Integrate transcriptomic data
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learning methods (e.g., predictive modelling, clustering, multivariate integration) to large-scale time series and sensor datasets. Contributing to the development of risk models and decision-support tools
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computing environment that includes GPU clusters, large-memory servers, and an NVIDIA DGX B200 system. These resources support the training of large multimodal models involving audio, video, language
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Job Posting Title: Postdoctoral Research Fellow, Department of Information, Risk, and Operations Management ---- Hiring Department: Department of Information, Risk, and Operations Management
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modelling, CFD mesh generation in complex 3D geometries. Proficient in handling large data sets and the ability to analysis and interpret results. Experience in commercial CFD package such as FDS and ANSYS