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learning, generative AI or LLM-based systems, cloud computing, and the design and validation of algorithms for high-volume quantitative or sensor-derived data. Experience with wearable data, health
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, Toronto Metropolitan University is on a transformative path to become Canada’s leading comprehensive innovation university. Integral to this path is the placement of equity, diversity and inclusion as
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Priority may be given to the following designated employment equity groups: women, Indigenous Peoples* (First Nations, Inuit and Métis), persons with disabilities and racialized persons
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artificial intelligence and machine learning (AI/ML) models that predict therapeutic response, identify clinically actionable patient subgroups, and support personalized treatment strategies. Through
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | about 3 hours ago
guidelines to experimental design. You will also learn how to communicate research findings effectively, bridging the gap between bench science and regulatory policy. Your training and acquired skill set will
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knowledge-grounded reasoning with flexible machine learning Tools that reduce manual burden while preserving traceability and clinical interpretability This position offers the opportunity to publish novel
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high-quality evidence that informs policy, practice, and innovation in the early childhood sector. We are seeking a Research Fellow to contribute to our research in developmental science and AI in
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research for project titled: “Automated Loose Baggage Handling System for Narrow-Body Aircraft (NYALA)”. Key Responsibilities: Work on exciting robotics design Simulation in physics-based-framework such as
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disciplines. Undertaking stakeholder engagement and co-designing activities with project partners. Mentoring and supervising higher degree by research students and early career researchers. Translating research
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relationships and apply data-driven or machine learning approaches to guide molecular design and accelerate materials discovery Collaborate with internal and external stakeholders, including computational, data