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Field
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application programming interfaces (APIs), through rigorous simulations and proof-of-concept (PoC) trials. This position is ideal for a researcher with a passion for solving complex problems at the intersection
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chronic illness. CEQL fosters interdisciplinary collaboration, mentorship, and innovation to address complex health challenges through rigorous scientific inquiry, implementation science, and community
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thinking and a deep interest in the relationship between storytelling, popular culture and social change. You will be confident designing and managing your own research project, communicating complex ideas
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(ML), to help solve complex agricultural problems that also depend on collaboration across scientific disciplines and geographic locations. In addition, many of these technologies rely on the synthesis
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air temperature maps • Develop and train Graph Neural Network (GNN) and Long Short-Term Memory (LSTM) architectures to model complex spatial and temporal dependencies in urban microclimate data
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in mathematical modelling and Bayesian inference while learning from three collaborating chief investigators. You will also build your publication record and professional networks through seminars
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industry partners. This role offers the opportunity to lead elements of complex research programs, publish high-quality outcomes, support research funding applications, and mentor emerging researchers. Drive
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, for example: learning new scientific skills, making funding applications & Fellowships, supervision/teaching opportunities, training courses, conferences, collaborative networks & academic/industrial
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through participation in professional meetings and trainings and networking with experts. Mentor(s): The mentor for this opportunity is Linda Hansen ([email protected] ). If you have questions about the nature
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will be supervised by Dr. Aline Talhouk and other co-investigators and senior lab members, with access to an international network of clinical and scientific collaborators. Key Responsibilities Develop