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efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being for all
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foundational methods for integrating single-cell and clinical transcriptomes; and train, fine-tune, and validate deep learning models using multi-omics and imaging data to predict clinical outcomes such as
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skills, including statistical analysis using R, Python, SPSS, Stata, or equivalent software. • Experience with computational social science methods, including NLP, machine learning, LLMs, social media
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: You will participate in research and analytical activities involving FDA's domestic and global regulatory science mission. You will gain hands-on experience at the intersection of public health policy
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partners to apply findings. You will also help recruit and support your linked PhD student and participate in the programme's mentoring, learning and international activities. Skills and experience You will
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 8 hours ago
learning experience focused on the evolving global landscape of generic drug regulation, manufacturing, and supply chain dynamics. The research experience emphasizes comparative evaluation of international
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About the Opportunity About the Opportunity Northeastern University Pharmaceutical Industry Fellowships Program is a two-year experiential program designed to advance lifelong learning and the
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related field. Strong analytical and manuscript preparation skills, experience analysing complex clinical or biological datasets and the ability to develop well-documented code in R, Python or another
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through teaching, learning, research, and enterprise. An ambitious and innovative university, our research is designed to have real-world impact on society and tackle global challenges through our 16
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Intelligence & Machine Learning Develop machine learning and AI models to identify, predict and characterise genome instability patterns. Design generative and predictive computational models to infer mutational