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Field
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other life-threatening illnesses. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases
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to develop innovative analytical solutions, enhance research capability, and help create lasting impact through data-driven discovery. At UQ, you will be challenged, inspired and rewarded while contributing
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focus on developing and integrating modeling, co-design, and data-driven optimization methodologies for BS-PDN-enabled systems, including 3DIC and chiplet-based architectures. This position offers
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be sent to [email protected] with the subject line: Postdoctoral Application - DOE Genesis Forward Modeling Project. Interested applicants should submit: Cover letter describing research interests and
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Vision, Video Understanding, and Multimodal AI. Design AI models for concept-driven video understanding of consumer facial care behaviours. Work with PI and company to develop the AI solution Develop novel
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optimisation techniques, machine-learning methods and data-driven modelling. Familiarity with robotics and autonomous-system simulation environments such as ROS/ROS2, Gazebo, AirSim, Unity, or equivalent
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Water Research Centre (EEWRC) The Climate and Atmosphere Research Centre (CARE-C) The Science and Technology Driven Policy and Innovation Research Centre (STeDI-RC) Considerable cross-centre interaction
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Center for Drug Evaluation and Research (CDER) | Southern Md Facility, Maryland | United States | 4 days ago
. The fellow will collaborate with and learn from multidisciplinary FDA scientists to develop data-driven and first-principles models and evaluate how they can be used to improve understanding of pharmaceutical
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will play a key role in building a parallelized, agent-driven exploration system and integrating a multimodal detection pipeline, ensuring real-time performance, scalability, and deployment readiness in
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prediction of regional climate and extremes using hybrid physics-AI models. About the project/work tasks There is a growing need for subseasonal-to-seasonal (S2S; 2 weeks to 12 months) predictions of regional