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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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with AI interpretability techniques (attention visualization, model behavior analysis) ● Knowledge of hate speech detection models or adversarial NLP ● NLP Expertise: Experience with nltk, spaCy
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imaging, and clinical data governance; RAW image handling and smartphone Image Signal Processor (ISP) pipelines; Multimodal machine learning and Chinese NLP (e.g., Hugging Face Transformers); On-device
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technical discipline desired Minimum of five years’ software development experience with Python and SQL. Minimum of three years’ experience building pipelines to deploy NLP and deep learning models
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professional domains and a desire to ask big-picture questions. Preferred Qualifications: Familiarity with natural language processing (NLP) or network science. Experience with machine learning libraries like
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descriptions made by authors and peers. 3. Implementation and exploration of the analytical tools selected such as Whisper and CLIP (OpenAI), Cursor or similar, or NLP libraries for automated categorization. 4
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to track polarization and hate speech dynamics over time. • Advanced NLP for subtle language features: Detect irony, sarcasm, and other nuanced expressions using transformer-based models that integrate
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continuity. The ideal applicant will have experience in AI, ML or NLP in EHR data or a strong interest in applying these methods to primary care. This position will be primarily responsible for managing and
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, etc.), NLP, computer vision, or related fields is a plus Application Instructions: To be considered, please submit the following items along with your online application: CV Transcript(s) (unofficial is
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executable. This is a challenging research project at the intersection of AI, NLP, and software engineering, with applications in life sciences and beyond. We are looking for highly motivated applicants for a