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disciplines) Strong experience or demonstrated interest in AI, NLP, machine learning, or digital health research Experience working with clinical, communication, or patient-generated datasets is an asset
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Computer Science (or close field) with strong foundations in data management, machine learning, and software engineering. Coursework or projects in NLP/LLMs, information retrieval, knowledge graphs/ontologies, data
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), enabling cross-contextual learning and refinement of policy recommendations. A postdoc with expertise in urban built environment studies and qualitative social sciences will play an important role in
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large datasets analyses Active participation in LALP Lab activities Required selection criteria You must have completed a doctoral degree in cognitive science or computer design/programming Training and
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solver who wants to be part of a dynamic team. Information about the Church Lab: Learn more about the innovative work led by Dr. George Church here: https://churchlab.hms.harvard.edu/ , https
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and data integration. While machine learning and computational approaches may be applied where appropriate, the core emphasis of the role is on population-level data analysis, interpretation, and
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. Qualification requirements A PhD degree within neuroscience, psychology, medicine, machine learning or biology or equivalent. Doctoral dissertation must be submitted for evaluation by the closing date
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profiling, and other cutting-edge, high-dimensional tissue analysis approaches to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning
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four years are expected to acquire basic pedagogical competency in the course of their fellowship period within the duty component of 25 %. Place of work is Department of Chemistry at Blindern/Gaustad
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the foundation necessary to: identify the learning needs of diverse audiences create robust simulation cases and courses based on specific learning objectives develop and refine debriefing skills for all levels