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Details Title Postdoctoral Fellow in Deep Learning Theory and/or Theoretical Neuroscience School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position
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populations and biobanks for risk prediction, genetic discovery, and genomic medicine. Federated and transfer learning for distributed and privacy-preserving data integration. AI and Deep learning approaches
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required) Experience with machine learning / deep learning (PyTorch; model training; GPU workflows). Experience with Transformers / text embeddings / multimodal modeling (e.g., Hugging Face ecosystem
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genomic, epigenomic, and fragmentomic data, from patient liquid biopsy samples Design and evaluate deep learning models for MRD detection and characterization Collaborate with multidisciplinary teams across
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command of data wrangling, cleaning, and large-scale dataset management. Machine Learning/Deep Learning: Experience with PyTorch, TensorFlow, or Hugging Face; embedding models; and model validation
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evaluate deep learning models for MRD detection and characterization Collaborate with multidisciplinary teams across Dana-Farber Cancer Institute, the Broad Institute, and more Mentor and guide junior staff
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, Social Sciences , Biomedical Informatics , Causal Inference , Computational Social Science , Data Science and Information , Data Visualization , Deep Learning , High dimensional Data , Large Language
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translational medicine concepts Publication history in relevant fields (AI/ML, genetics, toxicology) Experience with deep learning frameworks and generative AI models (e.g., GANs, VAEs) Key Leadership
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on human behavior modeling related to video classification using deep learning networks for end-users. Work with other team members to develop and maintain software for maximum efficiency and usability
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departments. What you’ll do: Designing, developing, and deploying modern AI/ML models—including deep learning, foundation models, multimodal architectures, and generative approaches—to analyze complex