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of artificial intelligence for healthcare applications, medical image analysis, and human-centered computing systems, with a focus on cross-domain transfer learning and multi-modal data integration. Formulate
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-modal datasets (e.g., biological, imaging, environmental, or clinical data). Proficiency in programming languages such as Python, R, or MATLAB, and familiarity with machine learning frameworks (e.g
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health records (EHR), waveforms from bedside monitors, radiology images and wearable sensors. This position offers a unique opportunity to work closely with clinicians on applications of machine learning
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work with amazing partners, including other Harvard Medical School-affiliated hospitals. The qualified candidate will specifically focus on the analysis of large genomics datasets derived from cancer
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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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for detecting visual stress markers using underwater cameras, and other imaging modalities in industrial environments (RAS farm) Develop and validate pipelines for fish biometrics, posture and movement analysis
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in image processing, quantitative analysis, and biological interpretation Proficiency in AI/machine learning tools for image segmentation, transformation, registration, or tracking Solid mathematical
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integration and AI models tailored for fish behaviour, health, and stress signal analysis. Investigate and apply novel machine learning and deep learning techniques for pattern recognition, classification, and
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experience Evidence of experience with public-patient involvement and stakeholder engagement Track record in scientific publication and dissemination Experience with Machine Learning Algorithms and Artificial
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to these values ensures that we foster a culture of mutual respect, open collaboration, continuous learning, and innovative thinking. Join us at RCSI, where your contributions will be recognised, and you will be