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Details Title Postdoctoral Fellowship in Reinforcement Learning, Probabilistic Methods, and/or Interpretability School Harvard John A. Paulson School of Engineering and Applied Sciences Department
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Carnegie Mellon University, Institute for Computer-Aided Reasoning in Mathematics Position ID: 3637-PF [#27988] Position Title: Position Type: Postdoctoral Position Location: Pittsburgh
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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow in Machine Learning for Computational Pathology, Medical Imaging, and Clinical Text Analysis Department Bashashati
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clinical approaches, including: Histopathology and digital pathology (whole-slide imaging, WSI) Quantitative analysis of the tumour immune microenvironment AI-based image analysis, machine learning and deep
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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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highly interdisciplinary setting combining microbial mutagenesis assays, mammalian cancer models, next-generation sequencing, bioinformatics, and machine learning. Experimental data will be integrated with
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www.icord.org for more information. Additional information about Dr. Krassioukov‘s laboratory can be found at: http://icord.org/researchers/dr-andrei-krassioukov/. Work Performed: The postdoctoral fellows
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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Connections working at Johns Hopkins University More Jobs from This Employer https://main.hercjobs.org/jobs/21973320/low-vision-postdoctoral-fellowship-for-wilmer-eye-institute Return to Search Results
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, integrating and interpreting them across modalities remains a fundamental challenge. The successful candidate will develop computational and machine-learning frameworks for multimodal neuroscience data